- 5 ways humanitarian bots can save the world
- New data shows stronger outlook for adtech
- Xiaomi Mi Box review: A great entry point for Android TV and 4K streaming
- Universal basic income: If a robot takes your job, it could actually be good for you
- How Next Games stopped ad fraud in The Walking Dead: No Man’s Land
- The tech manager’s challenge: How to stay steeped in tech while focusing on leadership?
- France makes its bid to be recognized as a global AI hub
- 7 takeaways from the White House report on AI
- Samsung to include AI digital assistant in upcoming Galaxy S8
- Xbox One chainsaws all comers as consoles crush mobile game ad spending in October
- How a chatbot can help you save money
- How chatbots help with your marketing efforts
- $69 Pocket Chip DIY computer has 3D acceleration to run Quake III
Posted: 06 Nov 2016 12:10 PM PST
Fifteen year old Sarafina, a female student in the capital city of Liberia, had a distressing problem at school: Her math teacher refused to give her a report card unless she had sex with him.
Every day at school, he would request sexual favors and touch her inappropriately. Embarrassed, Sarafina kept the issue hidden from everyone, even her parents, until her father overheard a sexually harassing phone call the teacher made to their home. Sarafina's father successfully confronted the man and got the report card, but his daughter was reprimanded for reporting her teacher's sexual advances and forced to move to another school.
1. Bots can uncover the truth
In Liberia, teachers enjoy high social status but children, especially young girls, are culturally trained not to speak out, leading to a culture of silence and tolerance. While Sarafina's story sounds extreme to Westerners, her experience is painfully common yet largely ignored in her country.
Enter UNICEF's U-Report, a social reporting bot that enables young people in developing countries to report issues in their community via SMS and other messaging platforms. U-Report polled 13,000 users in Liberia to ask if teachers at their schools were exchanging grades for sex. An astonishing 86% of reporters said yes.
Within a week of the U-Report discovery of the "Sex 4 Grades" epidemic, help hotlines around the country were inundated with reports of child abuse. Simply exposing a pervasive taboo inspired victims to speak up and reach out for help. Since then, UNICEF and Liberia's Minister of Education have collaborated on a plan to stop the issue.
"U-Report is not just about getting questions answered, but getting answers back out," explains Chris Fabian, Co-Lead of UNICEF's Innovation Unit. "We get responses in real-time to use the data for policy change." With over 2.6 million U-Reporters worldwide and deep expertise building technology for developing economies, the U-Report team is uniquely positioned to tackle challenging social issues like violence against children, HIV/AIDs policy, climate change, and war and conflict.
2. Bots can raise awareness
Less than 50% of the population in Ethiopia has access to clean water and only 21% of the population enjoys proper sanitation services. Unfortunately, cold statistics like these rarely move people to take action.
That's why Charity:Water teamed up with Lokai and AKQA to create Yeshi, a Facebook Messenger chatbot that humanizes the water crisis in Ethiopia. Yeshi is a young girl in Ethiopia who walks 2.5 hours every day to the nearest reliable water source. She travels alone and straps huge plastic jugs to her back so she can bring gallons of water home to her family. You learn about her dreams of going to school and see a map of her journey.
Yeshi even asks you to send her a picture of where you live. "Wow! Our worlds are so different," she remarks, before leaving you to continue her arduous walk alone again.
The experience of "Walking With Yeshi" is undeniably emotional. Conversational experiences like this can be powerfully effective ways to convey the humanitarian challenges that face the global poor and inspire action.
Besides raising awareness, charities can also use bots and messaging platforms to raise critical funds. Charity: Water recently worked with Assist to enable donors to donate funds directly from Facebook Messenger.
3. Bots can fight bureaucracy and inequality
19-year-old Joshua Browder is no typical teenager. The Stanford Computer Science undergraduate has single handedly-beaten over 160,000 unfair parking tickets with his bot, Do Not Pay. The sophisticated "robot lawyer" also helps tenants fight negligent landlords and the homeless apply for much needed government support. Browder was inspired to help the most vulnerable segments of society acquire legal help they would otherwise never be able to afford.
"With parking tickets, the robot lawyer takes money from the government. However, so many government bureaucracies can be automated, like the DMV. Eliminating bureaucracy will actually save the government money," points out Browder. "In the UK, there is this really broken system where the government pays a lawyer to file an application back to the government for a homeless person to receive support. The government wastes so much money with the application process when they should just spent that money on houses."
Browder's vision for Do Not Pay extends far beyond simply fighting off parking tickets and filing for homelessness. While some aspects of the law, like bankruptcy, are complicated and unintuitive, many legal processes can be modeled as logical decision trees by computers. Browder's mission is to turn Do Not Pay into a legal bot platform where lawyers can identify aspects of the law that are automatable and create their own bots.
Government bureaucracy is so pervasive that many other bots have cropped up to simplify civic matters. Against the backdrop of election cycle drama, several voter registration bots – HelloVote, GoVoteBot, andVotePlz – emerged to allow voters to skip onerous and error-prone paperwork and register simply through SMS and Facebook Messenger.
While competition between most Silicon Valley companies is fierce, voter registration is not a zero-sum game where startups squabble over limited scraps. According to Sam Altman's VotePlz, only 54% of eligible young people were registered for the last presidential election and 10% of millennials aren't sure if they're even registered. Everyone is fighting for the same social goal: boost voter turnout and help citizens do their civic duty.
4. Bot can provide social and health services
With the threat of Zika looming over the Americas, knowing whether you've contracted the disease is critical to getting timely and adequate treatment. GYANT, a healthbot on Facebook Messenger, walks you through a questionnaire of symptoms to identify your likelihood of having Zika. Concerned users can get a personalized answer immediately rather than wait for a doctor's appointment or ignore the problem.
Many non-profits and government agencies offer hotlines and support groups faced with high demand and insufficient human staff. Some, like Samaritans, a suicide prevention group, are reportedly working on chatbots to offer faster response times and around-the-clock support. Such social support, whether given by human or bot, has a huge impact on people. Even gifting senior citizens with a robotic seal is shown to reduce stress and improve socialization. Besides simply building mechanical robots to address the physical challenges of old age, social chatbots can be built to address emotional and mental needs.
In the healthcare industry, providers are overwhelmed by the number of patients, most of whom need continued social and emotional support outside of their doctor and hospital visits. Sensely is a digital nurse bot with a human-like avatar that can save up to 20% of a clinician's time by monitoring whether patients are dutifully following their prescribed regimens.
For mental health, conversational avatars like Ellie, a digital therapist developed by USC's Institute of Creative Technologies, can interview patients and detect depression and anxiety by analyzing words, facial expressions, and tone. Professor Louis-Philippe Morency, co-creator of Ellie, says the bot cannot replace a human therapist, but is a decision support tool that helps to "gather and analyze an interaction sample" for doctors.
5. Bots can motivate the right actions
Can't kick your nicotine addiction but too embarrassed to nag a friend to help every time you feel a craving? Public Health England experimented with a Facebook Messenger bot for their month-long Stoptober campaign to help smokers quiet. Stoptober successfully helped 500,000 people quit smoking last year, an impressive 20% of the 2.5 million smokers who registered.
PHE's marketing director Sheila Mitchell believes the addition of the Facebook Messenger bot as a support tool for smokers will increase the % of successful quitters. "The heart of the campaign is social," explains Mitchell. "We found that the big numbers and responses come from social and that within this Facebook is absolutely dominant."
Where humanitarian bots fall short
Addressing social issues requires emotional sensitivity, a critical skill that bots are universally missing. LawBot is a legal bot created by Cambridge University students to help users in the UK understand the complexities of the law and identify whether a crime has been committed. Users can use the bot to report rape, sexual harassment, injuries and assaults, and property disputes.
Unfortunately, the bot uses a strict checklist to assess if a "crime" has been committed. If your report of sexual harassment doesn't fit within preset criteria, the bot responds with the following: Despite good intentions, the emotionally insensitive LawBot quickly dismisses sexual harassment if the harassment does not fit within a narrow set of legal technicalities.
According to the Guardian, over half of women in the UK have been sexually harassed at work. Even if the offending actions don't fit a neat legal box of being a "crime," unwanted aggressions can cause lasting psychological damage and unnecessary suffering. Additionally, many corporate cultures discourage reporting to avoid expensive legal battles or PR nightmares.
When a bot bluntly tells a potential victim of sexual harassment that "no crime was committed here" without a detailed understanding of the situation, the results can be counterproductive and further discourage victims to speak up. Even if LawBot deems that a proper crime has occurred to you, the bot's only response is to send you the address of the nearest police station.
While artificial intelligence technologies have not yet evolved for bots to respond with emotional acuity to difficult situations, a better solution for LawBot is to connect distressed users to sympathetic hotlines, support groups, or expert human lawyers once the conversation has exceeded the bot's domain expertise.
Help bots develop empathy and compassion
Do Not Pay's Browder cautions that "the really big challenges are ones that require compassion and human judgment. If someone is to be granted bail, there is no set criteria. Bots work really well when there is a clear decision tree." When bots address ambiguous issues, like rape or sexual harassment, even well-intentioned efforts like LawBot risk backfiring.
Many technology powerhouses are working to give bots the emotional sensitivity needed to make complicated judgements that can't simply be captured with decision trees. As mentioned earlier, digital therapists like Ellie factor in facial expressions and vocal characteristics. Amazon is working to make Alexa, the cloud AI that powers the Amazon Echo, detect and respond to your emotions. SRI International, the research lab which created Apple's SIRI, is building new virtual assistants that emote just like you do.
"Humans change our behavior in reaction to how whoever we are talking to is feeling or what we think they're thinking. We want systems to be able to do the same thing," says William Mark, head of SRI International's Information and Computing Sciences Division.
Even the emotionless bots of today have changed the world for the better, from revealing epidemics of violence against young girls (U-Report) to automating government bureaucracies like homeless applications (Do Not Pay). Bots can tell stories to help you empathize with humanitarian crises (Yeshi), assist your healthcare providers (GYANT, Ellie, Sensely), and help you quit your worst habits (Stoptober).
We can't wait to see what the emphatic and compassionate bots of the future will do.
This article appeared originally at Topbots. Used with permission.
Posted: 06 Nov 2016 11:08 AM PST
Earlier in the year I wrote about the schizophrenic state of the adtech market. I addressed the peculiar situation in which adtech funding was difficult to come by and the IPO market was shut, but levels of strategic M&A remained relatively robust. Those conditions were driven in large part by new entrants to the sector, and that trend has not abated over the course of 2016. However, there are further reasons why the outlook for the industry is positive, and certainly more so than some commentators have portrayed.
As we hurtle towards year end, VC funding in adtech remains in short supply. However, the Q3 data my company recently released shows that, as in 2015 and despite caution around the sector from financial investors, strategic interest remains strong and M&A activity remains healthy.
Total adtech deal volume rose 44 percent, from 27 deals in Q2 to 39 deals in Q3, and the quarter was book-ended by two mega-deals (Verizon's acquisition of Yahoo and Orient Hontai Capital's $1.4 billion majority acquisition of AppLovin).
The public markets also showed some signs of reopening, as Q3 saw the first adtech IPO in over a year, The Trade Desk. In sharp contrast to most of the adtech companies that went public in the 2013-14 period, The Trade Desk has both scale and strong profitability and is currently trading 38 percent ahead of its IPO price.
The adtech sector would appear to be on an upwards trajectory as we move into Q4. There are clearly a number of reasons to be cheerful. Here are just a few:
1. There are lots of buyers
A total of 215 companies have been acquired in the sector over the past 18 months, and, significantly, those deals were completed by 186 different buyers. That's 186 separate companies that recognize the strategic significance of having adtech capabilities.
Forty-two percent of those 215 deals were done by pureplay adtech companies, such as AppNexus, Criteo, and MediaMath. These deals were primarily driven by consolidation of geographies, tech or channels, or were mergers between smaller players looking for scale.
A further 11 percent were completed by marketing services groups, such as WPP's acquisitions of Essence and Exchange Lab, and Denstu’s buy-up of Accordant. So that's 53 percent of deals being done by the "usual suspects."
That means nearly half of deals – 47 percent – are being done by new entrants into the sector, and that is what lies behind the buoyancy in the M&A market. These deals are being completed by a who's who of the TMT ecosystem. Very few technology and media companies can ignore the fact that the way we all consume (and pay for) media is being disrupted. Broadcasters, telcos, traditional data players, and of course the enterprise software groups have all made acquisitions into the sector, and each month seems to bring another new entrant.
One notable group of new buyers, who weren't particularly visible even as recently as January this year, are the Asian acquirers. Adtech deals completed by buyers from the APAC region have increased by more than 30 percent in the first three quarters of 2016 compared to 2015. Miteno, Orient Hontai Capital, and Spearhead are all examples of Asian companies that have acquired Western adtech assets since the beginning of the year. We expect this trend to continue.
2. Strategic multiples are achievable
There's no denying average valuations in adtech have declined over the past couple of years, but the average masks a very clear distinction between strategic and non-strategic deals. We are still seeing strategic valuations being achieved across a wide variety of propositions — identity, user-generated content, mobile, video, data and AI, to name a few. The common denominator across all the high multiple deals is scarcity value – either because the target is one of only a few companies globally with its particular capability or because it has achieved exceptional scale and therefore moves the needle for large buyers.
Interestingly, many of the highest multiple deals have been in scenarios where the buyer and target were already working together in commercial partnership. The synergies are proven and the deal de-risked.
3. Convergence with martech
The martech market continued to perform strongly in Q3. Our index of public company stocks is up 21 percent since the beginning of the year. Equally, M&A continues to be strong, with deal volume for the first three quarters of the year up around 19 percent.
Much has been made of the convergence between adtech and martech, but true cross-over M&A between the two sectors has been relatively limited. The two revenue models do not mix easily – sticky, scalable subscription revenue for martech, transactional revenue models for adtech, often with no direct client relationship.
However, recent deals such as Oracle's acquisition of AddThis and Salesforce's purchase of Krux continue to bring the major “marketing clouds” ever closer to pure audience building and media buying. SAP has chosen to build its own DMP and DSP with the recent launch of SAP Exchange Media. As we look ahead to 2017, we expect this convergence to pick up pace, as the lines between advertising and marketing continue to blur.
This increased convergence is as much an opportunity as a threat. Advertising represents over half of most large enterprises' marketing budgets, and it is the adtech vendors, media agencies, and publishers who understand that world.
No one can deny that adtech has been through a tough time over the past couple of years. However, I see parallels with the cycle many new disruptive technology markets experience: Too much money goes into the sector; the market corrects as investors get their fingers burned; and then it emerges stronger and more stable, with the strongest companies coming to the fore. We are certainly seeing the signs that adtech is entering that phase of maturity.
This means those adtech companies that have the right capital structure in place and a clear grasp of their own economics are now in a position to thrive. In the meantime, the ever-expanding pool of buyers in the sector continues to underpin relatively healthy M&A prospects for the right companies.
Julie Langley is a Partner at Results International.
Posted: 06 Nov 2016 09:58 AM PST
When Android TV was introduced to the world back in 2014, the new TV-focused operating system wasn’t packaged as a new entertainment platform as such, but more of an upgrade to its old (failed) Google TV initiative. It sought to bring cohesion to Android content across devices.
“We’re simply giving TVs the same level of attention phones and tablets have had,” explained Android director of engineering David Singleton at the launch.
Over the past couple of years, Android TV has arrived on a number of smart TVs and set-top boxes — including the now-discontinued Google Nexus Player — as Google strives to ensure its presence extends beyond your mobile devices into the centerpiece of your living room.
Though Android TV has generally been well received, it has yet to make a big splash, and it could even be argued that Google is fighting an uphill battle against another of its own TV-focused products, the Chromecast. Last month, however, China-based technology giant Xiaomi launched an intriguing product in partnership with Google, representing Xiaomi’s first ever product launch in the U.S.: the Mi Box, an Android TV set-top box (STB). The contraption essentially brings all the goodness of Android to your TV, and includes music- and video-streaming services such as Netflix, Spotify, YouTube, and Google Play, and crucially it supports 4K-quality video and HDR. Throw into the mix the $69 pricetag, and Xiaomi’s first foray into the U.S. TV market seemed like a pretty tempting proposition.
VentureBeat has gotten its proverbial mitts on the Xiaomi Mi Box, and here are our thoughts on the device and whether it’s worth 69 of your hard-earned dollars.
What you get
For those interested in the specs, the Mi Box packs a quad-core ARM Cortex-A53 2.0 GHz processor, 2GB of RAM, 8GB of flash storage, and comes with Android 6.0 Marshmallow out of the box.
At 101mm x 101mm x 19.5mm, the Mi Box is a fairly unobtrusive, palm-sized square contraption accompanied by a voice-enabled remote.
There are just a handful of ports on the back of the Mi Box: a power adapter port, HDMI port (HDMI cable is included), USB 2.0 port, and 3.5mm audio output port.
Unfortunately, there is no micro USB port to power the box off a USB connection on the TV as you can do with a Chromecast, so you will need to power this from an electrical outlet.
Thankfully, the Mi Box remote, which connects to the Mi Box over Bluetooth, isn’t saturated with buttons and is fairly straightforward to master.
There is a power button, the familiar Android “back” and “home” buttons, a directional control pad with a “select” button in the middle, a volume up/down button, and a button to action voice commands.
Powered by two standard AAA batteries, the remote connected flawlessly with the Mi Box during the initial setup, and worked without interference at all times.
Software, interface, and content
Setting up the Mi Box is a breeze, and the on-screen guide walks you through the process of connecting the device to your home Wi-Fi.
The Mi Box interface, much like other Android TV devices and smart TVs in general, is media-focused with a bunch of suggested apps popping up to get you started, including Hulu, Netflix, HBO Now, and Spotify.
As a slight aside here, the Mi Box does allow you to edit the homescreen, thankfully, meaning you can hide apps that are of no interest to you, or shift things around a little to prioritize ones you’re likely to use more often.
The voice-search feature on the Mi Box was pretty good, and for those not hooking a Bluetooth keyboard up to the device, that’s a godsend compared to the fiddly nature of using a remote to manually type in search terms through the on-screen keyboard.
Simply tap the microphone button on the remote, and the TV screen will let you know that it’s all ears.
You can then say something fairly generic such as “the latest action movies” or “funny films,” and the Mi Box will tap the smarts of natural-language processing (NLP) to serve up a bunch of comedies to watch.
Equally, you can say something like “film suitable for children”…
… or “films made in the 1980s” to quickly find something to watch.
Voice commands can also be used for general web searches, including news and weather forecasts, meaning the Mi Box takes on the role of a sort of smart assistant for your living room, though admittedly it’s not quite on a par with something like Amazon’s Echo, which integrates with a myriad of smart home devices.
The Mi Box launch was packaged as a partnership between Xiaomi and Google, a signal that Google is striving to ensure consistency in design and usability across the board. This is a good thing for sure, but it’s worth noting here that this tight control also means that the Android TV Google Play Store doesn’t have all the apps you’ll be used to on Android elsewhere.
Indeed, there are specific requirements a developer must adhere to when making their apps available for TVs — they can’t simply port a tablet app over to the TV realm, even though the underlying structure is the same. The way a user interacts with a TV interface is different to that of a mobile device, with remote controls, keyboards, and mice — rather than fingers — the more common input device. Moreover, a TV viewer may be situated a considerable distance from the screen, so the interface must reflect this.
In short, if you’re on the hunt for an Android TV device, such as the Mi Box, thinking that it serves up the same access to the Google Play Store as your Samsung Galaxy S7, then you’ll be disappointed. The selection of games and apps is still fairly limited, and those hoping to find Amazon Video nestled in nicely alongside Netflix will be particularly disappointed.
For the more technically minded, there are alternative ways to install Android apps beyond that of Google Play. You can extract an app’s APK file to a remote disk such as a USB stick and sideload it onto Android TV in a similar way as you would with an Android phone or tablet.
Mi Box: impressions and further thoughts
Having used the Mi Box for a few weeks, I was generally impressed with the device’s capabilities, particularly for the $69 price tag. For those already signed up to the Android ecosystem on mobile, it offers an affordable conduit to replicate much of the experience on their big-screen TV.
There are many comparisons to be made between the Mi Box and other similar devices, including the Nvidia Shield Android TV console. But weighing in at $200, and with a focus on gamers, the Shield has its sights firmly set on a particular audience.
Moreover, given that people are increasingly turning to smart TVs with apps already built in, there will be limited desire to procure an Android TV device if all someone wants is access to the popular video-streaming apps. And gamers would likely look elsewhere (for example, the Nvidia Shield).
For the price, the most obvious comparison for me is actually Google’s Chromecast. While the existing incarnation costs a mere $35, the upcoming turbo-charged Chromecast, launching later this month, costs exactly the same as the Mi Box. And it will also support 4K content.
I would see little incentive to upgrade to the Mi Box from my current second-generation Chromecast… if it wasn’t for the fact that the Mi Box supports 4K streaming. That is a mighty tempting proposition, but as noted already the soon-to-launch Chromecast v 3.0 will support 4K too.
So what’s the better option of the two?
Chromecast has no screen-based interface and it has no remote control — it requires a mobile device to be present at all times to control the on-screen action. With a dedicated remote control, a proper interface that everyone in the room can see, and pretty nifty voice-command smarts, the Mi Box feels like a more natural device for the living room, one that visitors and the whole family can use. Then there’s this little nugget: The Mi Box has Google’s Cast technology built in, meaning this is basically a Chromecast and Android TV box combined into one.
With the Mi Box, Xiaomi has a compelling device that targets a mass-market audience with an affordable price. Whether it’s the right device for you really depends on your current TV arrangement and what you’re looking for.
If you’re already on the hunt for a device to turn a standard non-smart TV into something with a higher IQ, then the Mi Box is certainly worth your money. But for those who already have a smart TV as a centerpiece in their lounge, be it a Sony Bravia or a Samsung, I just don’t see enough of a pull with Android TV in general to merit paying $69 to “upgrade.”
The same goes for those with a Chromecast or Roku plugged into their TV — there aren’t enough extras here to justify adding another device to your living room setup. But if you want 4K streaming and a more family-friendly interface, then it’s worth the investment.
Posted: 06 Nov 2016 09:05 AM PST
"Reply to the important email from your boss."
"Wear that blue-colored dress today, it matches your new shoes."
"Go to Tahiti on vacation, there is a good price now for tickets for this destination."
All of these pieces of advice and more come from AI assistants. A wide range of these assistants have emerged to make our lives better: big ones like Amazon's Alexa, Apple's Siri, and SoundHound and multiple startups that are trying to conquer the market. Alterrа, for example, will help you choose the country for your next vacation. Luka helps you make plans together and pick places to eat. Findo helps find emails, files, tickets, and notes across personal clouds and mailboxes. Cubic Robotics is an intelligent butler for home management. And thanks to Realty Editor, you can control physical objects, such as lighting devices, technology, or a vehicle, with your smartphone.
Our AI friends will not only take care of us but will also take over our jobs. Last month, Uber launched its very first fleet of self-driving cars in Pittsburgh, PA. The company expressed hopes of completely replacing its existing fleets with driverless cars by 2030. This news spurred economic and industry experts to consider the potential of sky-rocketing unemployment rates in the country due to AI. Financial experts at the White House forecasted that soon all workers earning an hourly wage of less than $20 will be replaced by AI. If you talk real figures, this means that around 350 million employees belonging to the production, warehouse, or service industry will lose their jobs.
These statistics have given rise to a blatant controversy that is pushing for a plausible solution. And one recommended solution is the universal basic income (UBI). According to the suggested UBI policy, every citizen in the country would be entitled to a fixed amount of money distributed by the government regardless of their level of income or job status. This fixed amount would have to be sufficient for subsistence. According to a recent story in The Economist, the UBI can be calculated on the revenue collected through tax as a percentage of the GDP. Based on that calculation, today the US government would pay a basic income of $6,300 annually (that’s $525 a month) to every citizen.
A number of countries are considering the idea of or actually putting the theory of UBI to the test. Finland, for example has initiated a two-year trial period where each individual will get $600 a month as basic income. In addition to that, Sam Altman (former Y Combinator president and venture capitalist) is testing something similar. He writes in his blog:
Right now, a team led by Altman is in the process of piloting an experiment in Oakland that looks at human behavior when individuals do not have to work for survival. If the pilot is successful, the team plans to move ahead with a long-term, five-year study.
Previously, experiments on mice have shown that, when their existence was largely unneeded, the entire population often becoming extinct. How does that translate for humans?
In ancient Greece, when everyone had slaves — even the poorest families — there was a thriving culture of science and arts as free citizens focused on being creative. But in our modern-day scenario, with AI assistants looking after our basic needs, would we all just become their pets or would we again turn creative? The Altman experiment in Oakland could help answer that question.
Guaranteeing that everyone in the country receives enough income to afford basic goods and services, governments can ensure that everyone has food and shelter. The greatest criticism of the UBI idea is that, with a guaranteed basic income, people will lose their motivation to work. Critics fear that we could become pets to our AI assistants as a result.
That would be a logical criticism if money were the only motivation for people to work. If we look at the scenario in connection with Maslow's hierarchy of needs, we can see that people have five different levels of needs, and they are all motivators. The UBI would only fulfil the most basic physiological needs. Needs that are higher up the pyramd — safety, belonging, esteem, and self-actualization — would still motivate people to work.
I’m not just making it up; there's proof. Consider the state of Alaska, which has been practicing something very close to the concept of the UBI since 1982. The Alaska Permanent Fund invests money in a diversified asset portfolio, and the earnings are distributed among the residents of the state. Since implementation of the policy, the state has created more than 10,000 new jobs. And there is no sign the dividends have pushed citizens of the state to work any less than they previously did.
Another example is the UBI pilot project in Namibia. When the country began distributing a basic income to its citizens, there was a drastic change in the behavior of the population. The UBI led to greater employment rates as people created jobs for themselves, the general poverty levels dropped 18 percent, and the crime rate plummeted 36.5 percent. There was also a 29 percent increase in general income levels (this increment was exclusive of the basic income distributed). Just like Alaska, Namibia reported an improvement in general wellbeing of the society with the implementation of the basic income grants.
Back in March of 2014, a group of individuals took par in a psychology experiment. Each participant had the choice of solving either two or three puzzles. Some participants had the additional choice of not participating in the activity at all. The results showed that participants who were given the choice of not participating spent about seven minutes on each of their chosen puzzles compared to the five minutes spent by the other lot. So when given an option of not to work, people genuinely seem to prefer to work rather than staying idle – and with greater commitment.
So will humans become lazy and uncreative if robots take our jobs and the government gives us a universal basic income?
The answer is no.
When you provide people with a basic income, you put them all on the same level. They may not have to worry about hunger or shelter, but anyone who chooses to work can bring in additional income. Those who don't work would earn less than those who do. This could, in fact, lead to a decrease in unemployment as people work towards achieving their needs beyond physiological requirements.
Gary Fowler is CEO and cofounder of smart search assistant Findo. He has 25 years of experience advising numerous international companies and startups as well as extensive experience with fundraising through a successful IPO (CKSW). He is also founder of Fowler International, an international business development consulting company that works with companies interested in entering the Russian/CIS market, and cofounder of GVA LaunchGurus and Broadiant. He speaks frequently in Eastern Europe and has received several awards for excellence in the region including the 2013 Co-Chairman of the Year Award from the American Chamber of Commerce.
Posted: 06 Nov 2016 08:02 AM PST
You could say that a lot of the users in The Walking Dead: No Man’s Land mobile game were zombies. That’s because they just weren’t human.
Next Games discovered that hundreds of thousands of users provided by several advertising networks weren’t real people. It uncovered them using analytics tools from marketing intelligence firm Tune. This is just one case in many that illustrates the extent of advertising fraud. Ad fraud is expected to cost digital advertisers more than $7.2 billion in 2016, according to a study by White Ops and the Association of National Advertisers.
Annina Salvén, finance director at Finland’s Next Games, said in an interview with GamesBeat that her company has saved hundreds of thousands of dollars by uncovering fake users supplied by four ad networks out of the 17 the company used. It wasn’t easy figuring out who was fake because the company had more than 50 million players in the past year, and it’s not easy to figure out which players were bots and which were human.
Next Games launched No Man’s Land in September 2015 on iOS and on Android in October 2015. That coincided with the launch of the sixth season of The Walking Dead TV show, and it was a huge hit. With the launch of season seven a couple of weeks ago, Next Games went all out in recruiting new players. It linked the launch of new content to events that happened within the show’s episodes.
“We brought on more ad networks to reach new kinds of users to build traffic for our game,” said Salvén. “It’s important for us to have the tools to discern what is valuable traffic.”
Next Games used Tune’s tools to analyze the number of clicks from odd places. The traffic from these sources was 100 times what they saw elsewhere from some more established partners. Next Games shut off the ad networks and communicated with them. That stopped the bad installs and Next Games recouped some of its losses. But it also helped Next Games determine why the fraud was happening. (Salvén declined to identify the ad networks that sent the fraudulent users for legal reasons.)
“Next Games is taking a mature approach,” said Peter Hamilton, CEO of Tune, in an interview with GamesBeat. “They are trying to fully understand what happens with the partners they work with. Rather than scrubbing the traffic, they can go further and look at different behaviors.”
Hamilton said Tune’s tools aim to provide as much transparency as possible for the traffic.
“The whole industry is incentivized to get a lot of downloads from any source, as everybody just wants downloads.
The analytics came in handy because Next Games has just 70 people, mostly focused on developing games — not stopping fraud. The Walking Dead game was popular in part because it was based on the popular TV show. But as some players drop out, the game company had to start advertising to get players back or get new ones on board. Every game experiences this type of churn over time.
But when you’re advertising to get millions of players, it’s hard to spot traffic patterns that are unhealthy. Next Games was able to evaluate the quality of its traffic and understand the scale of the problem. With the three to four ad networks that seemed suspicious, the amount of money at risk was substantial at about $200,000. Tune’s marketing intelligence tool helped detect and evaluate abnormal patterns in the data.
“The added complexity comes with such a large information technology operation,” Salvén said. “You may get real traffic, but you might wind up paying for traffic that should be properly classified as organic or traffic that you would have gotten anyway without the advertising. For two of the networks, we saw the amount of clicks start [to] exponentially grow to levels we had not witnessed with any other network.”
Next Games sent the data to the ad networks and said it would stop working with them. They got some money back and then set up new protocols for onboarding ad networks. Now, Next Games can flag potential problems earlier.
Tune’s tools try to figure out which ad network to give credit when someone installs a game. Did that individual install it because of an ad that they viewed just before, or could the install be credited to more than one advertising channel?
“Should the credit go to the ad partner who provides the last click or the first click? And what did the user do after they installed the game? Did they ever play the game at all,” Hamilton said.
Indeed, many users are “ghosts” who never open an application after installing it. It’s a complex problem, and sometimes, the answers remain mysteries. Just about every ad network has some kind of fraud, but Tune’s job is to sniff out the major problems, Hamilton said. Sometimes the fraud is geographic, where a lot of users show up in one country, but all of the advertising takes place in a different country.
“Most fraud tools don’t tell you what causes them to reject a particular install,” Hamilton said. “They give you a list. One instance doesn’t mean anything. But patterns tell you what you need to know. We look at how much money was spent on the providers and who sent traffic that didn’t look right.”
The way to catch the fraudsters is to run a bunch of tests with a sufficient amount of the traffic.
Salvén said, “We may not catch them all. We know that with the more sophisticated tools we have, the more sophisticated the fraud will become. But we want to get as much transparency as possible.”
Posted: 06 Nov 2016 07:02 AM PST
A workplace dynamic I've always found fascinating is the instinctual need for people to size up the technical depth of a technology leader upon first introduction. The technologists in the room want to determine if the manager understands what they do on a daily basis. The non-technical people want to judge if she'll be able to communicate clearly, or if she speaks in technical gibberish.
This social dynamic is a natural side effect of the dual nature of the senior technology leadership role. Technology managers must create and operate code and infrastructure, which requires detailed, technical knowledge, while also translating technical concepts into business strategy and managing a team, which requires communication and leadership skills.
Technology depth vs. leadership excellence
As a technology manager, you can never be too technical. A deep, hands-on understanding of technology gives you superpowers because:
But, that said, a good manager has to put their leadership responsibilities first. If you spend too much time diving deep and actually building the product, then you're spending less time performing your responsibilities as a leader, which include cultivating a professional network, understanding changing business needs, and implementing long-lasting improvements.
So what’s a technology manager to do? Shift their focus away from technical details altogether and simply embrace becoming the pointed-haired boss they were always destined to be?
Resolving the paradox
For me, the solution to this paradox comes from an unlikely source — Greek mythology. In The Myth of Sisyphus, Existentialist writer Albert Camus argued that you need to live your life under the illusion that a universal notion of right or wrong exists. Sisyphus was a Greek king who was punished with endlessly pushing a giant boulder up a steep hill, only to have it roll back down after he reached the top, repeating this cycle for eternity. For Camus, the myth of Sisyphus illustrated the human dilemma: We must move forward in life, working under the illusion that a universal Truth exists, only to be smacked in the face every so often by remembering that our notion of Truth is a lie. Rather than roll over when this realization happens, we must move forward.
I see Camus' argument as a blueprint for tackling the paradox of technology leadership. As leaders, we must relentlessly strive to learn new technologies, knowing deep down that we'll never be able to master them. Fortunately, for the curious-minded, endlessly learning new technology is more like bouncing a beach ball across a field than pushing a heavy boulder up a hill.
So how can we help ourselves learn new technology without being consumed by it, to the detriment of our leadership responsibilities?
Below are some of methods I've found effective:
Cultivate a hacker's mindset
Most importantly, technology leaders should always cultivate a hacker's mindset. Hacking is the tangible manifestation of technical curiosity. A good hacker is always experimenting, exploring new technologies, and getting her hands dirty. Granted, you may never be the best engineer in the company, but you'll certainly be on your way to becoming one of its best leaders.
Jake Bennett is CTO at POP, a Seattle-based creative technology agency that has worked with such companies as Starbucks, Pokémon, Target, Microsoft, and Major League Soccer. Follow him on Twitter: @jakebenn.
Posted: 06 Nov 2016 03:34 AM PST
Disclosure: Organizers of the “France is AI” conference paid travel expenses for the reporter to attend and moderate several sessions at the event.
Tucked into a courtyard in central Paris, the 35 employees of Snips are hunched over their computers trying to put the finishing touches on a new version of the company’s artificial intelligence app for smartphones.
The company is packed full of big brains, many of them products of France’s leading universities and a culture that is historically strong in mathematics. And they’re not afraid to let you know it. Etched into winding wooden staircases that lead to Snips offices are a series of math puzzles that job recruits are asked to solve as they work their way upstairs.
Snips’ app wants to scan all the data across the apps on your smartphones to deliver insight about you and eventually become a hyper-smart personal assistant. But it promises to take a privacy-friendly approach by keeping all the data on your phone, where it will do the processing, rather than hoovering data up into the cloud.
The complex underbelly of algorithms is based on technology developed by the three cofounders, all French and all holding PhDs with strong backgrounds in data science. The company faces enormous competition as giants like Google and Apple build more AI into their mobile products, but Snips still managed to raise $6.5 million in venture capital earlier this year.
“How can you create a digital alter ego?” asks Rand Hindi, Snips cofounder and CEO, who has a PhD in bioinformatics. “It becomes a question of collecting as much data as possible so that it learns as much about your life as possible. But if we don’t have an answer for privacy, we can’t gain the trust of users.”
Snips is one of France’s most buzzed-about startups, but for the moment it’s still flying below the global radar. The same could be said, in many ways, of the country’s entire AI ecosystem. As France tries to build a reputation as a startup nation, there is still an assumption outside the country that its strengths probably lie with its traditional industries of food, fashion, luxury goods, and entertainment.
In fact, the country also happens to have one of the world’s largest machine learning and artificial intelligence communities, something that is obscured by the fact that many of the best and brightest are hired away by the world’s largest tech firms. But within France, there are now at least 180 AI startups, according to data compiled by the Paris-based venture capital firm ISAI. And these companies are hoping that there will be enough breakout stars among them to cement the country’s reputation as a global AI hub.
“France is one of most vibrant ecosystems when it comes to artificial intelligence,” said Paul Strachman, the U.S.-based venture partner for ISAI . “But it’s not really known outside of France. And sometimes it’s not really known inside France.”
AI by the numbers
The U.S. is far out in front when it comes to the size and funding of its artificial intelligence and machine learning startups. Over in Europe, London is still considered the continent’s leading AI hub.
Between January 2014 and mid-October 2016, 111 AI-related companies in the U.K. raised $342 million in venture capital, according to data crunched by Nathan Benaich, an investor at Playfair Capital in London. There were 8 AI-related exits in that time worth a combined $900 million, according to Benaich’s numbers.
Most importantly, Google acquired London-based DeepMind in January 2014, a headline-grabbing deal that shone a spotlight on the country’s machine learning and AI chops. DeepMind’s AI technology is already being baked into a wide range of the Google’s products.
By the numbers, France lags the U.K. During that same period, 33 AI-related companies in France raised $108 million. There were three exits worth about $22 million, according to Benaich’s data.
“In Europe, the U.K. is definitely the front-runner, and that after there’s France,” Benaich said. “And after that, it's a very steep drop. It’s still super early days for this industry. But 90 percent of financing and exit events are happening in the States.”
France isn’t completely invisible. Just as the U.K. had its DeepMind moment with Google, France got its own Silicon Valley shout-out last year when Facebook announced it was opening its global AI Research center in Paris. “France already has one of the strongest AI research communities in the world, so we think this is the ideal home for our new team,” CEO Mark Zuckerberg wrote at the time. “I’m excited for us to be taking another step toward the future of computing and connecting the world.”
Facebook had previously hired French native Yann LeCun, a New York University professor, to be director of its AI research group in 2013. And in 2015, Facebook acquired Wit.ai, a Palo-Alto based natural language processing startup launched by three French graduates of Paris’ École Polytechnique that became an integral part of the company’s new chatbot platform for Messenger.
Of course, this highlights both France’s opportunity and its challenge. There is a reservoir of talent, but many of its brightest leave for places like the U.S. or the U.K. Even many startups that begin in Paris migrate their headquarters overseas. As a result, many of these successes reflect back on France.
That’s why, Strachman argues, France is still underappreciated when it comes to AI and machine learning. In early September, Strachman, who was born in France and now lives in New York, organized a two-day conference and workshop in Paris called “France Is AI.”
At the event, Strachman listed a number of the assets that he felt were creating strong momentum across the French AI scene.
These start with the wide range of French universities and research institutions that are churning out groundbreaking work and a flood of graduates. These include the French Institute for Research in Computer Science and Automation, a national institution that has placed a heavy emphasis on AI across its 160 projects being conducted across eight research centers, and the French National Center for Scientific Research (CNRS), which has about 600 researchers at two of its research centers focused on fundamental math and informational science problems.
This has started to attract corporate AI investment from around the world, including Japan’s ecommerce leader Rakuten, which has opened an AI research center in France. The groundswell of talent has also created some of the largest meetup groups, such as the Paris Machine Learning Group, which counts 4,000 members. And they are running some of the largest open source code libraries for AI, such as SciKit Learn.
“France is quite visible in the academic perspective when you look at machine learning,” said Alexandre Gramfort, assistant professor at Telecom Paris Tech.
From outside academia, however, not so much. That academic prowess does not always spill into the commercial world. Much of France’s academic community prefers to keep its distance from industry. The tight links between Stanford University and Silicon Valley are harder to forge here. For those who do graduate and want to go into the commercial sector, they’re often hired by Google, Twitter, or Salesforce to work elsewhere.
However, there are some signs of a shift. Strachman said his firm is now tracking 180 AI-related startups in France that work in a wide range of industries, including medicine, self-driving vehicles, and consumer.
Igor Carron, founder of the Paris Machine Learning Startup, has launched a startup called LightOn, which is building an optics-based computing system for AI. Last month, autonomous bus platform Navya raised $33.4 million. And earlier this year, Shift Technology of Paris raised $10 million from investors to build out its AI-driven insurance fraud detection platform.
“We are dealing with insurance only,” said Shift’s chief strategy officer Eric Sibony. “We don’t do general AI. And that’s what helped us convince investors.”
Probably the prototype for this emerging generation of French AI startups is Tinyclues, which so far has raised about $7.3 million in venture capital. The company was founded in 2010 to help ecommerce sites to use machine learning algorithms for targeting marketing campaigns.
One of the founders, David Bessis, was a mathematics researcher at CNRS and Yale before leaving academia to launch a startup. He said bridging that academic-commercial divide has not always been easy, but as France produces more successful startups, Bessis said it’s developing talent that can help AI startups do just that. In Tinyclues’ case, the company hired a product developer from Criteo, one of the country’s biggest breakout tech stars in recent years.
“France has been weak in terms of product development, but strong in terms of engineering,” Bessis said. “We have to learn and improve in that respect. But now we can leverage other people’s success to help us do that.”
Ultimately, however, what is going to determine whether France makes it onto anyone’s AI map is the ability to produce success stories. And in this case, that means some notable exits. Earlier this year, Paris-based Moodstocks was acquired by Google for its machine vision technology for an undisclosed sum. The team subsequently joined the R&D center Google opened in Paris which, among other things, includes a focus on AI.
Strachman, for his part, is hoping that such developments will slowly help build that reputation. It’s not out of a sense of ego or national pride, he said. But rather, he’s hoping that as more international VCs recognize France for its AI potential, more investment money will flow into the startups that are struggling to attract the resources they need to compete on a global basis.
“The ambition for the entrepreneurs that I’ve talked to in this space is really, really huge,” he said. “The more VCs know about the strengthening of AI and France, the easier it will be for them to raise money. We just have to continue to tweak that perception.”
Note: Here are two videos produced summing up the France Is AI event:
Posted: 05 Nov 2016 10:24 PM PDT
The White House released a much-anticipated document last May entitled "Preparing for the Future of Artificial Intelligence." Sent from the Office of the President and the National Science and Technology Council Committee on Technology (or NSTC), the report is 58 pages of research, documentation, and recommendations on how the United States government plans to respond to artificial intelligence (AI) moving forward.
The report was developed by the NSTC's Subcommittee on Machine Learning and Artificial Intelligence, "which was chartered in May 2016 to foster interagency coordination, to provide technical and policy advice on topics related to AI, and to monitor the development of AI technologies across industry, the research community, and the Federal Government," according to the report.
The NSTC hosted five public workshops, as well as putting out a public Request for Information. The information drawn from those six sources informed the eventual recommendations of the committee. As it says in the report, there’s an "attempt to reach General AI by expanding Narrow AI solutions [that] have made little headway over many decades of research."
The 23 official recommendations can be boiled down into seven broad mandates, which serve as a good guide for anyone in the field. These seven declarations will have a noticeable impact on the future of technology in the U.S., and everyone in the industry should be familiar with them, in order to take best advantage of the new opportunities they will open (and the doors they may close).
1. AI should be used for public good
AI has already begun providing major dividends to the public in fields such as healthcare, transportation, criminal justice, and the economy.
One concrete example is AI-enabled traffic management, which can reduce wait times and unnecessary carbon emissions by as much as 25 percent. In animal welfare and research circles, animal migration tracking is being improved by analyzing photographs that tourists post to social media. In the future, we hope to see vast improvement in the criminal justice system, including in the areas of crime reporting and bail sentencing.
So what are the concrete steps we need to take, moving forward? The government recommends that both private and public institutes invest in research to see how their specific business or industry would benefit from AI. There are also plans to create an open-source AI training database to ensure everyone has access to the technology necessary to embark on this new phase.
2. Government should embrace AI
AI generally makes things faster and more efficient, and every agency should be on board. DARPA has an educational system to create a digital tutor for Navy recruits, and the recommendation is for that tutor to be adapted for every agency.
In tandem with this proposal, the government has announced more federal support for AI research. The private sector will be the main engine, but government needs to support both underfunded basic research and the kinds of long-term research in which the private sector is notoriously uninterested.
3. Automated cars and unmanned aircraft need regulation
New regulation is needed for two reasons: to protect the public and to ensure fairness in economic competition.
The cases of automated vehicles (such as self-driving cars) and unmanned aircraft (drones) are prime examples of areas that require immediate regulations. The Safety Standards that exist for automobiles need to be updated to include their automated cousins, and the wording of regional and federal laws needs to change to allow for new permutations. The U.S. government should also invest in developing and implementing an advanced and automated air traffic management system.
Creating appropriate regulations means finding senior people in the industry to shape and create those new laws. The government will work to develop a federal workforce with diverse perspectives in order to ensure fairness.
4. No child left behind
Most people have already heard Obama's speech about empowering the next generation. This recommendation states that all American students, from kindergarten through high school, will — as the report says — "learn computer science and be equipped with the computational thinking skills they need in a technology-driven world."
America needs to build and sustain a researcher workforce, including computer scientists, statisticians, database and software programmers, curators, librarians, and archivists with specialization in data science.
It isn't only about teaching AI, however; it's also about teaching safe AI. To that end, schools and universities will need to include technology-focused ethics and related topics in security, privacy, and safety as an integral part of curricula on AI, machine learning, computer science, and data science.
5. Use AI to supplement, not supplant, human workers
"A 2015 study of robots in 17 countries found that they added an estimated 0.4 percent to those countries' annual GDP growth between 1993 and 2007," according to the report. However, there is also the threat that AI will replace the workforce. Generally speaking, automation threatens lower-wage jobs and could potentially increase the wage gap. While the report does not yet have a suggestion for how to fix this problem, its authors do firmly declare that a solution needs to be found, and the recommendation is to study the problem in earnest and search for its solution.
That said, there is ample evidence that AI is used to its best effect when it works in tandem with human workers, rather than by replacing them. In one recent study, when trying to determine whether lymph node cells contained cancer, "an AI-based approach had a 7.5 percent error rate, where a human pathologist had a 3.5 percent error rate; a combined approach, using both AI and human input, lowered the error rate to 0.5 percent," according to the report. It seems we are stronger together.
6. Eliminate bias from data, or don't use it at all
The use of data needs to be combined with justice, fairness, and accountability. Artificial assistants are trained in a closed world, but then they are moved to an open world, and that change needs to be anticipated and planned for.
Take, for instance, the criminal justice system, where machine learning can help make huge strides for good. "The biggest concerns with Big Data are the lack of data, and the lack of quality data,” according to the report. If data is incomplete or biased, AI can actually exacerbate problems, rather than fixing them. No one wants a machine deciding if they're a flight risk if it doesn’t have the information to make an informed decision.
Another area where bias can be a huge problem is in something like job application screening. In the U.K., it is illegal to deny someone a job based on a decision made by a computer; thinking in the U.S. is that the computer had better know what it's about.
7. Think safe, think global
One of the most important conclusions in the document is that long-term concerns about super-intelligent general AI should have little impact on current policy.
The recommendation is about allowing trade secrets without allowing secrecy. The report suggests that if competition drives commercial labs toward increased secrecy, it may become more difficult to monitor progress and ensure ethical standards are being met. To that end, the authors suggest defining milestones and logging whether companies have surpassed them as a way to keep an eye on progress without divulging sensitive information.
The government also outlines a plan to monitor other countries. The idea is to develop a government-wide strategy on international engagement related to AI and to develop a list of AI-topical areas that need international engagement and monitoring. Japan, Korea, Germany, Poland, the U.K., and Italy are specifically listed as countries to partner with to this end.
The most important things companies need to be aware of are potential financing buckets for organizations that support ethics in AI and AI training, the creation of public milestones with which companies will no doubt need to engage, and new accountability standards for the creators of AI. Overall, the report has a hopeful tone, and the future seems clear. AI is here to stay, and the United States is embracing it with enthusiasm, tempered only mildly with caution.
Posted: 05 Nov 2016 08:47 PM PDT
(Reuters) – Samsung Electronics Co Ltd said on Sunday it would launch an artificial intelligence digital assistant service for its upcoming Galaxy S8 smartphone, seeking to rebound from the Galaxy Note 7’s collapse and differentiate its devices.
The world’s top smartphone maker in October announced the acquisition of Viv Labs, a firm run by a co-creator of Apple’s Siri voice assistant program. Samsung plans to integrate the San Jose-based company’s AI platform, called Viv, into the Galaxy smartphones and expand voice-assistant services to home appliances and wearable technology devices.
Samsung is counting on the Galaxy S8 to help revive smartphone momentum after the discontinuation of fire-prone Galaxy Note 7s, which will hit its profit by $5.4 billion over three quarters through the first quarter of 2017. Investors and analysts say the Galaxy S8 must be a strong device in order for Samsung to win back customers and revive earnings momentum.
Samsung did not comment on what types of services would be offered through the AI assistant that will be launched on the Galaxy S8, which is expected to go on sale early next year. It said the AI assistant would allow customers to use third-party service seamlessly.
“Developers can attach and upload services to our agent,” said Samsung Executive Vice President Rhee In-jong during a briefing, referring to its AI assistant.
“Even if Samsung doesn’t do anything on its own, the more services that get attached the smarter this agent will get, learn more new services and provide them to end-users with ease.”
Technology firms are locked in an increasingly heated race to make AI good enough to let consumers interact with their devices more naturally, especially via voice.
Alphabet’s Google is widely considered to be the leader in AI, but others including Amazon.com, Apple and Microsoft Corp have launched their own offerings including voice-powered digital assistants.
(Reporting by Se Young Lee and Nataly Pak; Editing by Andrew Hay)
Posted: 05 Nov 2016 06:04 PM PDT
Machine Zone has a convoy, but the consoles have the big numbers
GamesBeat has partnered with iSpot.tv, which measures TV advertising in real-time, to bring you a monthly report on how gaming brands are spending. The results below are for the top five spending gaming industry brands in October.
Gaming brands spent an estimated $101.6 million on TV ads in October. In total, 44 brands ran 129 ads 22,538 times on national TV, generating 4.1 billion TV ad impressions. Though the leaderboard is heavily dominated by console brands, Machine Zone rounded out the chart in fifth place.
Here's how each of the top brands deployed their TV advertising budgets:
Posted: 05 Nov 2016 05:00 PM PDT
While most people want to save more, the vast majority have a hard time putting money aside to meet their own savings goals. In fact, a recent survey found that as many as 63 percent of Americans are unable to set aside enough money (at least $1,000) to cover unexpected or emergency expenses.
But there is no need to panic if your account balance isn't exactly where you hoped it would be. You can now get help from an unexpected source — AI-powered bots provided by your bank. If you walk into a bank branch and ask how you can adjust your spending habits to save more, chances are you'll get blank stares in return. If you call with the same question, you’ll likely be transferred from department to department. Eventually, you may be offered an opportunity to meet with a financial adviser who can help you build an investment portfolio.
With the vast amounts of your personal data being collected and stored by your bank — including balances, transactions, and payments — you'd think your bank would be able to offer you better and more customized guidance along your path to financial success. But meeting your financial goals is more about changing behavior — your personal spending and savings patterns — than it is about picking stock and bonds. And this attention to personal spending habits is something that is sorely missing in today's banking relationships.
That's where an AI-powered bot can be a game changer. Instead of speaking with a banker who just learned your name and who glanced at your balances and account history for 15 seconds before you started the conversation, you can now get the help of a bot that within 150 milliseconds can analyze your most relevant financial activity and suggest practical steps you can take to meet both short- and long-term financial objectives.
But a bot can do much more than just give advice and point you in the right direction. For most people, the real challenge is staying the course; it's just too easy to fall back on old habits. Unlike a banker, the bot is there at all times (forget 9 to 4 banking hours!) to monitor your spending and the progress you make on your savings over time. It can remind you to cut back on spending when you stray from your plan and pop up at just the right time with tips to help you boost your savings. This might mean advising you when a large deposit is received or before you go on your usual weekend spending spree.
But the big question is, are bots ready to step up to the plate with such heavy responsibility? Many banking experts claim bots are not yet ready for prime time. Facebook revealed that over 30,000 bots have been created since it opened up its Messenger platform to third-party developers in April 2016. As expected, this bot gold rush has turned up a lot of dust with just a few nuggets. Examples of poorly designed bots are too easy to find, and many of them will make you giggle or shrug at their simplicity and lack of effectiveness.
While chatbots in financial services are new and will take time to mature, there are several skills they have to master on day one in order to be considered useful and trustworthy by customers.
Many of the bots we see today utilize simple natural language processing that seems cool at first but quickly falls apart as the conversation progresses. To carry an intelligent dialogue, the bot must be able to maintain the context of the conversation.
Here’s an example of a typical question a bot needs to be able to handle: How much did I spend on dining out in July? How about August?
At the same time, a bot has to be flexible enough to recognize that natural conversations don't always progress linearly — the bot must be able to process an unexpected reply and adapt to changes in the course of the conversation.
For a bot to be helpful, it needs to really know you. It’s not enough to simply access real-time financial data and history, it must also be able to analyze that information to understand your financial behavior and to come up with smart recommendations based on your personal goals. That's not a trivial task, and that's why bots need to be purpose-built — you can't expect a bot to know everything, but you want it to have deep knowledge of the issue you are trying to get help with.
As the bot gets to know you better, it must learn and get smarter over time. While banks are rightly guarded when it comes to letting AI run wild, machine learning is critical to helping the bot improve over time.
Ron Shevlin, director of research at Cornerstone Advisors and author of the book, Smarter Bank: Why Money Management Is More Important Than Money Movement, says financial institutions will have to deliver personalized guidance and advice through digital devices and channels if they want to gain consumers' trust and maintain their relationships.
If he and many other banking experts have it right, chances are it will not be long before your bank's bot steps in to help you save money and reach your financial goals.
Posted: 05 Nov 2016 04:10 PM PDT
Marketing in the 2000s was dominated by search engine marketing and optimization (SEM and SEO). The early 2010s saw the rise of Facebook and social media marketing. Most recently, we've seen mobile marketing rise and plateau as users have stopped downloading new apps. Now, we are entering the era of messaging and chatbots.
What is a "chatbot," you ask? Chatbots are computer programs that carry out conversations with people using a lightweight messaging app UI, language-based rules, or artificial intelligence. Chatbots converse with users using natural language (either voice or text) rather than traditional website or app user interfaces.
Consumer behavior has shifted from social networks to messaging platforms such as SMS, Facebook Messenger, Apple iMessage, Slack, and WeChat. The growth of the four largest messaging apps exceeds that of the four largest social networks. A new marketing channel is an exciting opportunity to experiment with fresh ad formats and connect with consumers in novel ways. Businesses also enjoy less competition, less ad fatigue, and potentially exponential returns on marketing investment dollars (ROI).
Here are the four critical ways chatbots are transforming marketing and how businesses can capitalize on the current conversational trend.
1. Engagement beyond clicks
In traditional online advertising, we call a click of an ad or play of a video "engagement." Engagement with a chatbot, on the other hand, is an active conversation with a user.
Disney created the Officer Judy Hopps bot on Facebook Messenger to tease the audience and drum up excitement prior to the movie's release. Instead of passively watching a movie trailer, users joined Judy on a detective hunt and experienced her interactive story firsthand. Engagement was astronomical: Users spent more than 10 minutes, on average, talking to the character, and countless users restarted the conversation to replay a different scenario.
Conversation and rapport-building is significantly more effective than a simple ad or video view. The interaction leaves users with an entertaining experience, a better understanding of the brand, and a positive emotional feeling. Many times, we see users enjoy the experience so much that they share it with friends (screenshotting conversations, updating profiles, linking in conversations), which is easy to do as these chatbots live on top of social networks.
2. Asking users specific questions
In this highly personal and conversational setting, chatbots can ask questions that couldn’t be fielded by traditional ads. Questions such as "Where do you live?" "What music do you like?" "Where's your dream travel destination?" or "What do you think of the latest Geico commercial?" are socially acceptable and even welcome in chatbot interactions.
A voter registration organization we partnered with used Facebook ads to drive users to a chatbot on Facebook Messenger. The chatbot asked the user a series of questions — such as name, address, and political affiliation — that the user happily answered. At the end of the interaction, the chatbot gave the user a completed Rock The Vote form link that was filled out based on the conversation. All the user had to do was click submit. This campaign more than tripled typical voter registration sign up rates. Rather than drive potential users to landing pages, companies are creating and driving users to chatbots for better engagement.
3. Opportunities for personalization
Ads have become more targeted over time. Brands are always seeking ways to appeal to users personally, whether through programmatic display ads, retargeting, or direct mail.
With chatbots, brands can personalize a conversation to the individual. Sephora's chatbot on Kik shares beauty tips with teenagers. The bot first inquires what users are interested in learning about — eyes, skin, hair, nails, etc. — and it only suggests relevant products, beauty tips, and tutorials. The Hello Hipmunk bot on Skype works with group chats: Travelers can plan trips with friends and family without ever having to leave the chat room.
Furthermore, businesses can remember and refer to personal information in future conversations to further customize a user's experiences. From simply referring to the user by name to connecting with their CRM, they can customize the conversational experience. Victoria's Secret PINK bot recommends specific styles of bras based on answers to an initial questionnaire. Wingstop's bot suggests new spicy offers to hot spice fanatics. In practice, companies must strike a responsible balance between personalization and privacy.
4. Bringing your brand personality to life
A branded chatbot becomes a "live entity" that can infuse personality into conversations. Disney's Miss Piggy bot is funny and sassy, while Universal Studio's Laura Barns Unfriended bot is angsty and foul-mouthed. The TMY.GRL bot from Tommy Hilfiger allows fashionistas to access exclusive behind-the-scenes fashion content. Traditional ads are "pushed" upon an unwilling or apathetic viewer, while chatbots "pull" users to engage with them.
Even B2B companies can participate. At Topbots, we created a corporate chatbot with our sense of humor to answer inquiries. Our bot is friendly and professional and even tells jokes as it answers questions 24/7. With our chatbot, we can show rather than tell our brand story to our audience. Strategically implemented and well-designed chatbots can tell your brand story, re-engage audiences, facilitate commerce, and grow your business.
Chatbots allow brands to connect with users on a deeper level, while also allowing users to feel in command of the conversation. Implemented strategically, bots can tell your brand's story to a limitless audience via an intimate one-on-one conversation. This has the potential to be a true game changer.
Posted: 05 Nov 2016 03:18 PM PDT
The $69 Pocket C.H.I.P. computer has gotten a software update that enables 3D acceleration on the ARM-based device. Now it can run games like Quake III.
The updated software and device are now available for holiday gift purchases. The Pocket Chip (spelled Pocket C.H.I.P. by the company) and its sister product Chip are targeted at the maker community — or do-it-yourself hardware enthusiasts who like to tinker.
Next Thing Co. has released an alpha image for the Pocket Chip that features a new Mali-400 3D acceleration driver.
A year ago, Next Thing Co. launched a $9 computer dubbed Chip. It has a 1-gigahertz ARM processor, 512 megabytes of main memory, built-in Bluetooth, Wi-Fi, and a battery. That device has sold more than 100,000 units.
“There’s pretty cool stuff happening in the community,” said Dave Rauchwerk, CEO of Next Thing Co., in an interview with GamesBeat. “I have seen the craziest things you’ve [ever] seen — like a $25 VR haptic glove.”
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