Don’t discount the game-changing power of the morphing “TV” when coupled with artificial intelligence (AI), natural language processing (NLP), and blockchain-based technologies!
When I saw the article below, I couldn’t help but wonder what (we currently know of as) “TVs” will morph into and what functionalities they will be able to provide to us in the not-too-distant future…?
For example, the article mentions that Seiki, Westinghouse, and Element will be offering TVs that can not only access Alexa — a personal assistant from Amazon which uses artificial intelligence — but will also be able to provide access to over 7,000 apps and games via the Amazon Fire TV Store.
Some of the questions that come to my mind:
Why can’t there be more educationally-related games and apps available on this type of platform?
Why can’t the results of the assessments taken on these apps get fed into cloud-based learner profiles that capture one’s lifelong learning? (#blockchain)
When will potential employers start asking for access to such web-based learner profiles?
Will tvOS and similar operating systems expand to provide blockchain-based technologies as well as the types of functionality we get from our current set of CMSs/LMSs?
Will this type of setup become a major outlet for competency-based education as well as for corporate training-related programs?
Will augmented reality (AR), virtual reality (VR), and mixed reality (MR) capabilities come with our near future “TVs”?
Will virtual tutoring be one of the available apps/channels?
Will the microphone and the wide angle, HD camera on the “TV” be able to be disconnected from the Internet for security reasons? (i.e., to be sure no hacker is eavesdropping in on their private lives)
The TVs will not only have access to Alexa via a microphone-equipped remote but, more importantly, will have access to the over 7,000 apps and games available on the Amazon Fire TV Store – a huge boon considering that most of these Smart TVs usually include, at max, a few dozen apps.
“I’ve been predicting that by 2030 the largest company on the internet is going to be an education-based company that we haven’t heard of yet,” Frey, the senior futurist at the DaVinci Institute think tank, tells Business Insider.
EdSurge profiles the growth of massive online open courses in 2016, which attracted more than 58 million students in over 700 colleges and universities last year.
The top three MOOC providers — Coursera, Udacity and EdX — collectively grossed more than $100 million last year, as much of the content provided on these platforms shifted from free to paywall guarded materials.
Many MOOCs have moved to offering credentialing programs or nanodegree offerings to increase their value in industrial marketplaces.
Alexa, Tell Me Where You’re Going Next— from backchannel.com by Steven Levy Amazon’s VP of Alexa talks about machine learning, chatbots, and whether industry is strip-mining AI talent from academia.
Excerpt:
Today Prasad is giving an Alexa “State of the Union” address at the Amazon Web Services conference in Las Vegas, announcing an improved version of the Alexa Skills Kit, which helps developers create the equivalent of apps for the platform; a beefed-up Alexa Voice Service, which will make it easier to transform third-party devices like refrigerators and cars into Alexa bots; a partnership with Intel; and the Alexa Accelerator that, with the startup incubator Techstars, will run a 13-week program to help newcomers build Alexa skills. Prasad and Amazon haven’t revealed sales numbers, but industry experts have estimated that Amazon has sold over five million Echo devices so far.
Prasad, who joined Amazon in 2013, spent some time with Backchannel before his talk today to illuminate the direction of Alexa and discuss how he’s recruiting for Jeff Bezos’s arsenal without drying up the AI pipeline.
What DeepMind brings to Alphabet — from economist.com The AI firm’s main value to Alphabet is as a new kind of algorithm factory
Excerpt:
DeepMind’s horizons stretch far beyond talent capture and public attention, however. Demis Hassabis, its CEO and one of its co-founders, describes the company as a new kind of research organisation, combining the long-term outlook of academia with “the energy and focus of a technology startup”—to say nothing of Alphabet’s cash.
…
Were he to succeed in creating a general-purpose AI, that would obviously be enormously valuable to Alphabet. It would in effect give the firm a digital employee that could be copied over and over again in service of multiple problems. Yet DeepMind’s research agenda is not—or not yet—the same thing as a business model. And its time frames are extremely long.
Silicon Valley needs its next big thing, a focus for the concentrated brain power and innovation infrastructure that have made this region the world leader in transformative technology. Just as the valley’s mobile era is peaking, the next frontier of growth and innovation has arrived: It’s Siri in an Apple iPhone, Alexa in an Amazon Echo, the software brain in Google’s self-driving cars, Amazon’s product recommendations and, someday, maybe the robot surgeon that saves your life.
It’s artificial intelligence, software that can “learn” and “think,” the latest revolution in tech.
“It’s going to be embedded in everything,” said startup guru Steve Blank, an adjunct professor at Stanford. “We’ve been talking about artificial intelligence for 30 years, maybe longer, in Silicon Valley. It’s only in the last five years, or maybe even the last two years, that this stuff has become useful.”
Artificial Intelligence (AI) and Machine Learning (ML) are two very hot buzzwords right now, and often seem to be used interchangeably. They are not quite the same thing, but the perception that they are can sometimes lead to some confusion. So I thought it would be worth writing a piece to explain the difference.
…
In short, the best answer is that:
Artificial Intelligence is the broader concept of machines being able to carry out tasks in a way that we would consider “smart”.
And,
Machine Learning is a current application of AI based around the idea that we should really just be able to give machines access to data and let them learn for themselves.
Yet, the truth is, we are far from achieving true AI — something that is as reactive, dynamic, self-improving and powerful as human intelligence.
…
Full AI, or superintelligence, should possess the full range of human cognitive abilities. This includes self-awareness, sentience and consciousness, as these are all features of human cognition.
Udacity is positioned perfectly to benefit from the rush on talent in a number of growing areas of interest among tech companies and startups. The online education platform has added 14 new hiring partners across its Artificial Intelligence Engineer, Self-Driving Car Engineer and Virtual Reality Developer Nanodegree programs, as well as in its Predictive Analytics Nanodegree, including standouts like Bosch, Harma, Slack, Intel, Amazon Alexa and Samsung.
That brings the total number of hiring partners for Udacity to over 30, which means a lot of potential soft landings for graduates of its nanodegree programs. The nanodegree offered by Udacity is its own original form of accreditation, which is based on a truncated field of study that spans months, rather than years, and allows students to direct the pace of their own learning. It also all takes place online, so students can potentially learn from anywhere.
The Great A.I. Awakening — from nytimes.com by Gideo Lewis-Kraus How Google used artificial intelligence to transform Google Translate, one of its more popular services — and how machine learning is poised to reinvent computing itself.
Excerpt:
Google’s decision to reorganize itself around A.I. was the first major manifestation of what has become an industrywide machine-learning delirium. Over the past four years, six companies in particular — Google, Facebook, Apple, Amazon, Microsoft and the Chinese firm Baidu — have touched off an arms race for A.I. talent, particularly within universities. Corporate promises of resources and freedom have thinned out top academic departments. It has become widely known in Silicon Valley that Mark Zuckerberg, chief executive of Facebook, personally oversees, with phone calls and video-chat blandishments, his company’s overtures to the most desirable graduate students. Starting salaries of seven figures are not unheard-of. Attendance at the field’s most important academic conference has nearly quadrupled. What is at stake is not just one more piecemeal innovation but control over what very well could represent an entirely new computational platform: pervasive, ambient artificial intelligence.
On [December 12th, 2016], Microsoft announced a new Microsoft Ventures fund dedicated to artificial intelligence (AI) investments, according to TechCrunch. The fund, part of the company’s investment arm that launched in May, will back startups developing AI technology and includes Element AI, a Montreal-based incubator that helps other companies embrace AI. The fund further supports Microsoft’s focus on AI. The company has been steadily announcing major initiatives in support of the technology. For example, in September, it announced a major restructuring and formed a new group dedicated to AI products. And in mid-November, it partnered with OpenAI, an AI research nonprofit backed by Elon Musk, to further its AI research and development efforts.
Whether Artificial Intelligence (AI) is something you’ve just come across or it’s something you’ve been monitoring for a while, there’s no denying that it’s starting to influence many industries. And one place that it’s really starting to change things is e-commerce. Below you’ll find some interesting stats and facts about how AI is growing in e-commerce and how it’s changing the way we do things. From personalizing the shopping experience for customers to creating personal buying assistants, AI is something retailers can’t ignore. We’ll also take a look at some examples of how leading online stores have used AI to enrich the customer buying experience.
Only 26 percent of computer professionals were women in 2013, according to a recent review by the American Association of University Women. That figure has dropped 9 percent since 1990.
Explanations abound. Some say the industry is masculine by design. Others claim computer culture is unwelcoming — even hostile — to women. So, while STEM fields like biology, chemistry, and engineering see an increase in diversity, computing does not. Regardless, it’s a serious problem.
Artificial intelligence is still in its infancy, but it’s poised to become the most disruptive technology since the Internet. AI will be everywhere — in your phone, in your fridge, in your Ford. Intelligent algorithms already track your online activity, find your face in Facebook photos, and help you with your finances. Within the next few decades they’ll completely control your car and monitor your heart health. An AI may one day even be your favorite artist.
The programs written today will inform the systems built tomorrow. And if designers all have one worldview, we can expect equally narrow-minded machines.
Some conference participants were concerned that this beleaguered region might grow. In fact, one attendee — an old friend who strategizes about technology for a big New York bank — commented that perhaps Wall Street would become “the new Rust Belt.” His concern was that automation of the finance industry would hollow out jobs in that field in the same way that robotics and other technologies have reduced manufacturing employment.
This is a sobering prospect, but there is plenty of evidence that it’s a real possibility. Key aspects of the finance industry have already been automated to a substantial degree. Jobs in the New York finance field have been declining for several years. According to data from research firm Coalition Ltd., more than 10,000 “front-office producer” jobs have been lost within the top 10 banks since 2011. Coalition also suggests that global fixed-income headcount has fallen 31% since 2011.
According to a new report, organizations are moving away from hierarchies, focusing on improving the employee experience, redesigning training, and reinventing the role of HR.
Business and HR leaders should rethink almost all of their management and HR practices as the proliferation of digital technologies transform the way organizations work, according to predictions for 2017 from Bersin by Deloitte, Deloitte Consulting LLP.
This year’s report includes 11 predictions about rapid technological, structural, and cultural changes that will reshape the world of work, including management, HR, and the markets for HR and workplace technology.
Artificial intelligence has a big year ahead — from cnet.com by Stepehn Shankland In 2017, AI won’t just be for the nerdy companies. Machine learning can help with mortgage applications and bridge safety, too.
Excerpt:
Get ready for AI to show up where you’d least expect it.
In 2016, tech companies like Google, Facebook, Apple and Microsoft launched dozens of products and services powered by artificial intelligence. Next year will be all about the rest of the business world embracing AI.
Artificial intelligence is a 60-year-old term, and its promise has long seemed like it was forever over the horizon. But new hardware, software, services and expertise means it’s finally real — even though companies will still need plenty of human brain power to get it working.
AI was one of the hottest trends in tech this year, and it’s only poised to get bigger. You’ve already brushed up against AI: It screens out spam, organizes your digital photos and transcribes your spoken text messages. In 2017, it will spread beyond digital doodads to mainstream businesses.
The design world has seen its own changes and updates as well. And as we know, change is the only constant. We’ve asked some of the top creatives to share what 2017 design trends they think will be headed our way.
SAN JOSE, Calif.–(BUSINESS WIRE)–The market has evolved from technologists looking to learn and understand new big data technologies to customers who want to learn about new projects, new companies and most importantly, how organizations are actually benefitting from the technology. According to John Schroeder, executive chairman and founder of MapR Technologies, Inc., the acceleration in big data deployments has shifted the focus to the value of the data. John has crystallized his view of market trends into these six major predictions for 2017…
2016 was a rich year for medical technology. Virtual Reality. Augmented Reality. Smart algorithms analysing wearable data. Amazing technologies arrived in our lives and on the market almost every day. And it will not stop in the coming year. The role of a futurist is certainly not making bold predictions about the future. No such big bet has taken humanity forward. Instead, our job is constantly analysing the trends shaping the future and trying to build bridges between them and what we have today. Still, people expect me to come up with predictions about medical technologies every year, and thus here they are.
Artificial intelligence (and machine/deep learning) is the hottest trend, eclipsing, but building on, the accumulated hype for the previous “new big thing,” big data. The new catalyst for the data explosion is the Internet of Things, bringing with it new cybersecurity vulnerabilities. The rapid fluctuations in the relative temperature of these trends also create new dislocations and opportunities in the tech job market.
The hottest segment of the hottest trend—artificial intelligence—is the market for chatbots. “The movement towards conversational interfaces will accelerate,” says Stuart Frankel, CEO, Narrative Science. “The recent, combined efforts of a number of innovative tech giants point to a coming year when interacting with technology through conversation becomes the norm. Are conversational interfaces really a big deal? They’re game-changing. Since the advent of computers, we have been forced to speak the language of computers in order to communicate with them and now we’re teaching them to communicate in our language.”
Google changed the world with its PageRank algorithm, creating a new kind of internet search engine that could instantly sift through the world’s online information and, in many cases, show us just what we wanted to see. But that was a long time ago. As the volume of online documents continues to increase, we need still newer ways of finding what we want.
That’s why Google is now running its search engine with help from machine learning, augmenting its predetermined search rules with deep neural networks that can learn to identify the best search results by analyzing vast amounts of existing search data. And it’s not just Google. Microsoft is pushing its Bing search engine in the same direction, and so are others beyond the biggest names in tech.
3 Forces Shaping Ed Tech in 2017— from campustechnology.com by Dian Schaffhauser
Ovum’s latest report examines the key trends that are expected to impact higher education in the new year.
Excerpts:
Institutions Will Support the Use of More Innovative Tech in Teaching and Learning
Schools Will Leverage Technology for Improving the Student Experience
The Next-Generation IT Strategy Will Focus More on IT Agility
We’ve seen a lot of exciting new innovations take place over the course of 2016. This year has introduced interesting new uses for virtual reality—like using VR to help burn victims in hospitals mentally escape from the pain during procedures—and even saw the world’s first revolutionary augmented reality game in the form of Pokémon Go. The iPhone 7 was also introduced, leaving millions of people uncertain of their feelings regarding Apple, while Samsung loyalists just prayed that their smartphones would stay in one piece.
Undoubtedly, there have been quite a few ups and downs in technology over the past year. With any luck, 2017 will provide us with even more new innovations and advancements in tech. But what exactly do we have to look forward to? TMC recently caught up with Jordan Edelson, CEO of Appetizer Mobile, to discuss his thoughts on 2016 and his predictions for what’s to come in the future. You can find the entire exchange below.
2016 is fast drawing to a close. And while many will be glad to see the back of it, for those of us who work and play with Virtual Reality, it has been a most exciting year. By the time the bells ring out signalling the start of a new year, the total number of VR users will exceed 43 million. This is a market on the move, projected to be worth $30bn by 2020. If it’s to meet that valuation, then we believe 2017 will be an incredibly important year in the lifecycle of VR hardware and software development. VR will be enjoyed by an increasingly mainstream audience very soon, and here we take a quick look at some of the trends we expect to develop over the next 12 months for that to happen.
Every December, we take a look back at big ideas from the past twelve months that promise to gain momentum in the new year. With more than eleven thousand projects launched between our Design and Tech categories in 2016, we have a nice sample to draw from. More importantly, we have a community of forward-thinking backers who help creators figure out which versions of the future to pursue. Here are some of the emerging trends we expect to see more of in 2017.
Everyday artificial intelligence
Whether chatting with a device as if it’s a virtual assistant strikes you as a sci-fi dream come true or a dystopian nightmare, we’re going to see an increasing number of products that use voice-controlled artificial intelligence interfaces to fit into users’ lives more seamlessly. Among the projects leading the way in this arena are Vi, wireless earphones that double as a personal trainer; Bonjour, an alarm clock that wakes you up with a personalized daily briefing; and Dashbot, a talking car accessory that recalls Kit, David Hasselhoff’s buddy from Knight Rider. One of the factors driving this talking AI boom is the emergence of platforms like Microsoft’s Cognitive Service, Amazon’s Alexa, and Google’s Speech API, which allow product developers to focus on user experience rather than low-level speech processing. For the DIY set, Seeed’s ReSpeaker offers a turnkey devkit for working with these services, and we’ll surely see more tools for integrating AI voice interfaces into all manner of products.
During Microsoft’s Build Conference earlier this year, CEO Satya Nadella delivered the three-hour keynote address, in which he highlighted his belief that the future of technology lies in human language. In this new wave of technology, conversation is the new interface, and “bots are the new apps.” While not as flashy as virtual reality nor as immediately practical as 3D printing, chatbots are nevertheless gaining major traction this year, with support coming from across the entire tech industry. The big tech enterprises are all entering the chatbot space, and many startups are too.
Out with the apps, in with the chatbots. The reason for the attention is simple: The power of the natural language processor, software that processes and parses human language, creating a simple and universal means of interacting with technology.
Developments in computing are driving the transformation of entire systems of production, management, and governance. In this interview Justine Cassell, Associate Dean, Technology, Strategy and Impact, at the School of Computer Science, Carnegie Mellon University, and co-chair of the Global Future Council on Computing, says we must ensure that these developments benefit all society, not just the wealthy or those participating in the “new economy”.
Artificial Intelligence (AI) is an important development and consumers globally will see it playing a much more prominent role — both in society and at work — next year, a new report said on Tuesday. Ericsson ConsumerLab, in its annual trend report titled “The 10 Hot Consumer Trends for 2017 and beyond”, said that 35 percent of advanced internet users want an AI advisor at work and one in four would like AI as their manager.At the same time, almost half of the respondents were concerned that AI robots will soon make a lot of people lose their jobs.
From driverless cars to robotic workers, the future is going to be here before you know it. Many emerging technologies you hear about today will reach a tipping point by 2025, according to a report from The World Economic Forum’s Global Agenda Council on the Future of Software & Society. The council surveyed more than 800 executives and experts from the technology sector to share their respective timelines for when technologies would become mainstream. From the survey results, the council identified 21 defining moments, all of which they predict will occur by 2030. Here’s a look at the technological shifts you can expect during the next 14 years.
… The first robotic pharmacist will arrive in the US 2021.
A new year is quickly approaching and Microsoft Research is offering a glimpse at what the tech scene has in store for 2017 along with some hints at the Redmond, Wash., tech giant’s own priorities for the coming year. This year, the company gathered prominent women researchers to share their thoughts on what to expect next year. Surprising nobody’s who’s been following Microsoft’s software and cloud computing strategy of late, the company is betting big on artificial intelligence (AI).
It’s still early days for the Internet of Things. As recently as 2014, 87 percent of consumers had never heard of the technology, according to Accenture. In 2016, and 19% of business and government professionals reported that they had never heard of the Internet of Things while 18% were only vaguely familiar with it, according to research from the Internet of Things Institute. Although the technology is getting the most traction in the industrial space, the most promising use cases for the technology are just starting to come to light. To get a sense of what to expect as we head into 2017, we spoke with Stanford lecturer and IoT author Timothy Chou, Ph.D.; Thulium.co CEO Tamara McCleary; industry observer and influencer Evan Kirstel; and Sandy Carter, CEO and founder of Silicon-Blitz.
15 tech trends in autonomous cars, artificial intelligence, and machine learning for 2017 — from venturebeat.com by John Brandon Tech is about to change dramatically next year. Want to stay up to date? These predictions from the famed design firm frog spell things out for you. In each section, a designer explains all of the details. Which one is already on your radar?
From DSC: Recently, my neighbor graciously gave us his old Honda snowblower, as he was getting a new one. He wondered if we had a use for it. As I’m definitely not getting any younger and I’m not Howard Hughes, I said, “Sure thing! That would be great — it would save my back big time! Thank you!” (Though the image below is not mine, it might as well be…as both are quite old now.)
Anyway…when I recently ran out of gas, I would have loved to be able to take out my iPhone, hold it up to this particular Honda snowblower and ask an app to tell me if this particular Honda snowblower takes a mixture of gas and oil, or does it have a separate container for the oil? (It wasn’t immediately clear where to put the oil in, so I’m figuring it’s a mix.)
But what I would have liked to have happen was:
I launched an app on my iPhone that featured machine learning-based capabilities
The app would have scanned the snowblower and identified which make/model it was and proceeded to tell me whether it needed a gas/oil mix (or not)
If there was a separate place to pour in the oil, the app would have asked me if I wanted to learn how to put oil in the snowblower. Upon me saying yes, it would then have proceeded to display an augmented reality-based training video — showing me where the oil was to be put in and what type of oil to use (links to local providers would also come in handy…offering nice revenue streams for advertisers and suppliers alike).
So several technologies would have to be involved here…but those techs are already here. We just need to pull them together in order to provide this type of useful functionality!
From DSC: After seeing the sharp interface out atAdobe (see image below), I’ve often thought that there should exist a similar interface and a similar database for educators, trainers, and learners to use — but the database would address a far greater breadth of topics to teach and/or learn about. You could even select beginner, intermediate, or advanced levels (grade levels might work here as well).
Perhaps this is where artificial intelligence will come in…not sure.
Today, we’re at the Windows Hardware Engineering Community event (WinHEC) in Shenzhen, China –where our OEM partners have created more than 300 Windows devices shipping in 75 countries generating more than 8 billion RMB in revenue for Shenzhen partners. We continue this journey with Intel, Qualcomm and hardware engineering creators from around the world. Together, we will build the next generation of modern PCs supporting mixed reality, gaming, advanced security, and artificial intelligence; make mixed reality mainstream; and introduce always-connected, more power efficient cellular PCs running Windows 10.
Nearly 140 private companies working to advance artificial intelligence technologies have been acquired since 2011, with over 40 acquisitions taking place in 2016 alone. Corporate giants like Google, IBM, Yahoo, Intel, Apple and Salesforce, are competing in the race to acquire private AI companies, with Samsung emerging as a new entrant in October with its acquisition of startup Viv Labs, which is developing a Siri-like AI assistant, and GE making 2 AI acquisitions in November.
Amazon.com Inc. unveiled technology that will let shoppers grab groceries without having to scan and pay for them — in one stroke eliminating the checkout line.
The company is testing the new system at what it’s calling an Amazon Go store in Seattle, which will open to the public early next year. Customers will be able to scan their phones at the entrance using a new Amazon Go mobile app. Then the technology will track what items they pick up or even return to the shelves and add them to a virtual shopping cart in real time, according a video Amazon posted on YouTube. Once the customers exit the store, they’ll be charged on their Amazon account automatically.
Online retail king Amazon.com (AMZN) is taking dead aim at the physical-store world Monday, introducing Amazon Go, a retail convenience store format it is developing that will use computer vision and deep-learning algorithms to let shoppers just pick up what they want and exit the store without any checkout procedure.
Shoppers will merely need to tap the Amazon Go app on their smartphones, and their virtual shopping carts will automatically tabulate what they owe, and deduct that amount from their Amazon accounts, sending you a receipt. It’s what the company has deemed “just walk out technology,” which it said is based on the same technology used in self-driving cars. It’s certain to up the ante in the company’s competition with Wal-Mart (WMT), Target (TGT) and the other retail leaders.
Alphabet Inc.’s artificial intelligence division Google DeepMind is making the maze-like game platform it uses for many of its experiments available to other researchers and the general public.
DeepMind is putting the entire source code for its training environment — which it previously called Labyrinth and has now renamed as DeepMind Lab — on the open-source depository GitHub, the company said Monday. Anyone will be able to download the code and customize it to help train their own artificial intelligence systems. They will also be able to create new game levels for DeepMind Lab and upload these to GitHub.
Beacon technology, which was practically left for dead after failing to deliver on its promise to revolutionize the retail industry, is making a comeback.
Beacons are puck-size gadgets that can send helpful tips, coupons and other information to people’s smartphones through Bluetooth. They’re now being used in everything from bank branches and sports arenas to resorts, airports and fast-food restaurants. In the latest sign of the resurgence, Mobile Majority, an advertising startup, said on Monday that it was buying Gimbal Inc., a beacon maker it bills as the largest independent source of location data other than Google and Apple Inc.
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Several recent developments have sparked the latest boom. Companies like Google parent Alphabet Inc. are making it possible for people to use the feature without downloading any apps, which had been a major barrier to adoption, said Patrick Connolly, an analyst at ABI. Introduced this year, Google Nearby Notifications lets developers tie an app or a website to a beacon to send messages to consumers even when they have no app installed. … But in June, Cupertino, California-based Mist Systems began shipping a software-based product that simplified the process. Instead of placing 10 beacons on walls and ceilings, for example, management using Mist can install one device every 2,000 feet (610 meters), then designate various points on a digital floor plan as virtual beacons, which can be moved with a click of a mouse.
Ask the Google search app “What is the fastest bird on Earth?,” and it will tell you.
“Peregrine falcon,” the phone says. “According to YouTube, the peregrine falcon has a maximum recorded airspeed of 389 kilometers per hour.”
That’s the right answer, but it doesn’t come from some master database inside Google. When you ask the question, Google’s search engine pinpoints a YouTube video describing the five fastest birds on the planet and then extracts just the information you’re looking for. It doesn’t mention those other four birds. And it responds in similar fashion if you ask, say, “How many days are there in Hanukkah?” or “How long is Totem?” The search engine knows that Totem is a Cirque de Soleil show, and that it lasts two-and-a-half hours, including a thirty-minute intermission.
Google answers these questions with the help from deep neural networks, a form of artificial intelligence rapidly remaking not just Google’s search engine but the entire company and, well, the other giants of the internet, from Facebook to Microsoft. Deep neutral nets are pattern recognition systems that can learn to perform specific tasks by analyzing vast amounts of data. In this case, they’ve learned to take a long sentence or paragraph from a relevant page on the web and extract the upshot—the information you’re looking for.
Facebook is powered by machine learning and AI. From advertising relevance, news feed and search ranking to computer vision, face recognition, and speech recognition, they run ML models at massive scale, computing trillions of predictions every day.
At the 2016 Deep Learning Summit in Boston, Andrew Tulloch, Research Engineer at Facebook, talked about some of the tools and tricks Facebook use for scaling both the training and deployment of some of their deep learning models at Facebook. He also covered some useful libraries that they’d open-sourced for production-oriented deep learning applications. Tulloch’s session can be watched in full below.
The Artificial Intelligence Gold Rush— from foresightr.com by Mark Vickers Big companies, venture capital firms and governments are all banking on AI
Excerpt:
Let’s start with some of the brand-name organizations laying down big bucks on artificial intelligence.
Amazon: Sells the successful Echo home speaker, which comes with the personal assistant Alexa.
Alphabet (Google): Uses deep learning technology to power Internet searches and developed AlphaGo, an AI that beat the world champion in the game of Go.
Apple: Developed the popular virtual assistant Siri and is working on other phone-related AI applications, such as facial recognition.
Baidu: Wants to use AI to improve search, recognize images of objects and respond to natural language queries.
Boeing: Works with Carnegie Mellon University to develop machine learning capable of helping it design and build planes more efficiently.
Facebook: Wants to create the “best AI lab in the world.” Has its personal assistant, M, and focuses heavily on facial recognition.
IBM: Created the Jeopardy-winning Watson AI and is leveraging its data analysis and natural language capabilities in the healthcare industry.
Intel: Has made acquisitions to help it build specialized chips and software to handle deep learning.
Microsoft: Works on chatbot technology and acquired SwiftKey, which predicts what users will type next.
Nokia: Has introduced various machine learning capabilities to its portfolio of customer-experience software.
Nvidia: Builds computer chips customized for deep learning.
Salesforce: Took first place at the Stanford Question Answering Dataset, a test of machine learning and comprehension, and has developed the Einstein model that learns from data.
Shell: Launched a virtual assistant to answer customer questions.
Tesla Motors: Continues to work on self-driving automobile technologies.
Twitter: Created an AI-development team called Cortex and acquired several AI startups.
IBM’s seemingly ubiquitous Watson is now infiltrating education, through AI powered software that ‘reads’ the needs of individual students in order to engage them through tailored learning approaches.
This is not to be taken lightly, as it opens the door to a new breed of technologies that will spearhead the education or re-education of the workforce of the future.
As outlined in the 2030 report, despite robots or AI displacing a big chunk of the workforce, they will also play a major role in creating job opportunities as never before.In such a competitive landscape, workers of all kinds, white or blue collar to begin with, should come readied with new, versatile and contemporary skills.
The point is, the very AI that will leave someone jobless, will also help him to re-adapt into a new job’s requirements.It will also prepare the new generations through the use of such optimal methodologies that will once more give meaning to the aging and counter-productive schooling system which has the students’ skills disengaged from the needs of the industry and which still segregates students into ‘good’ and ‘bad’. Might it be that ‘bad’ students become just like that due to the system’s inability to stimulate their interest?
From DSC: When I saw the article below, I couldn’t help but wonder…what are the teaching & learning-related ramifications when new “skills” are constantly being added to devices like Amazon’s Alexa?
What does it mean for:
Students / learners
Faculty members
Teachers
Trainers
Instructional Designers
Interaction Designers
User Experience Designers
Curriculum Developers
…and others?
Will the capabilities found in Alexa simply come bundled as a part of the “connected/smart TV’s” of the future? Hmm….
Amazon’s Alexa has gained many skills over the past year, such as being able to read tweets or deliver election results and fantasy football scores. Starting on Wednesday, you’ll be able to ask Alexa about Mars.
The new skill for the voice-controlled speaker comes courtesy of NASA’s Jet Propulsion Laboratory. It’s the first Alexa app from the space agency.
Tom Soderstrom, the chief technology officer at NASA’s Jet Propulsion Laboratory was on hand at the AWS re:invent conference in Las Vegas tonight to make the announcement.
Amazon today announced three new artificial intelligence-related toolkits for developers building apps on Amazon Web Services
At the company’s AWS re:invent conference in Las Vegas, Amazon showed how developers can use three new services — Amazon Lex, Amazon Polly, Amazon Rekognition — to build artificial intelligence features into apps for platforms like Slack, Facebook Messenger, ZenDesk, and others.
The idea is to let developers utilize the machine learning algorithms and technology that Amazon has already created for its own processes and services like Alexa.Instead of developing their own AI software, AWS customers can simply use an API call or the AWS Management Console to incorporate AI features into their own apps.
AWS Announces Three New Amazon AI Services Amazon Lex, the technology that powers Amazon Alexa, enables any developer to build rich, conversational user experiences for web, mobile, and connected device apps; preview starts today
Amazon Polly transforms text into lifelike speech, enabling apps to talk with 47 lifelike voices in 24 languages
Amazon Rekognition makes it easy to add image analysis to applications, using powerful deep learning-based image and face recognition
Capital One, Motorola Solutions, SmugMug, American Heart Association, NASA, HubSpot, Redfin, Ohio Health, DuoLingo, Royal National Institute of Blind People, LingApps, GoAnimate, and Coursera are among the many customers using these Amazon AI Services
Excerpt:
SEATTLE–(BUSINESS WIRE)–Nov. 30, 2016– Today at AWS re:Invent, Amazon Web Services, Inc. (AWS), an Amazon.com company (NASDAQ: AMZN), announced three Artificial Intelligence (AI) services that make it easy for any developer to build apps that can understand natural language, turn text into lifelike speech, have conversations using voice or text, analyze images, and recognize faces, objects, and scenes. Amazon Lex, Amazon Polly, and Amazon Rekognition are based on the same proven, highly scalable Amazon technology built by the thousands of deep learning and machine learning experts across the company. Amazon AI services all provide high-quality, high-accuracy AI capabilities that are scalable and cost-effective. Amazon AI services are fully managed services so there are no deep learning algorithms to build, no machine learning models to train, and no up-front commitments or infrastructure investments required. This frees developers to focus on defining and building an entirely new generation of apps that can see, hear, speak, understand, and interact with the world around them.
UK government is driving the artificial intelligence agenda, pinpointing it as a future technology driving the fourth revolution and billing its importance on par with the steam engine.
The report on Artificial Intelligence by the Government Office for Science follows the recent House of Commons Committee report on Robotics and AI, setting out the opportunities and implications for the future of decision making. In a report which spans government deployment, ethics and the labour market, Digital Minister Matt Hancock provided a foreword which pushed AI as a technology which would benefit the economy and UK citizens.
“Ethics often falls behind the technology,” says Voithofer of Ohio State. Personal data becomes more abstract when it’s combined with other datasets or reused for multiple purposes, he adds. Say a device collects and anonymizes data about a student’s emotional patterns. Later on that information might be combined with information about her test scores and could be reassociated with her. Some students might object to colleges making judgments about their academic performance from indirect measurements of their emotional states.
A world where DNA can be rewritten to fix deadly diseases has moved a step closer after scientists announced they had genetically-edited the cells of a human for the first time using a groundbreaking technique.
A man in China was injected with modified immune cells which had been engineered to fight his lung cancer. Larger trials are scheduled to take place next year in the US and Beijing, which scientists say could open up a new era of genetic medicine.
The technique used is called Crispr, which works like tiny molecular scissors snipping away genetic code and replacing it with new instructions to build better cells.
Can you be sexually assaulted in virtual reality? And can anything be done to prevent it? Those are a few of the most pressing ethical questions technologists, investors and we the public will face as VR grows.
The scope of Alphabet’s ambition for the Google brand is clear: It wants Google’s information organizing brain to be embedded right at the domestic center — i.e. where it’s all but impossible for consumers not to feed it with a steady stream of highly personal data. (Sure, there’s a mute button on the Google Home, but the fact you have to push a button to shut off the ear speaks volumes… )
In other words, your daily business is Google’s business.
“We’re moving from a mobile-first world to an AI-first world,” said CEO Sundar Pichai…
But what’s really not OK, Google is the seismic privacy trade-offs involved here. And the way in which Alphabet works to skate over the surface of these concerns.
What he does not say is far more interesting, i.e. that in order to offer its promise of “custom convenience” — with predictions about restaurants you might like to eat at, say, or suggestions for how bad the traffic might be on your commute to work — it is continuously harvesting and data-mining your personal information, preferences, predilections, peccadilloes, prejudices… and so on and on and on. AI never stops needing data. Not where fickle humans are concerned.
Welcome to a world without work— from by Ryan Avent Automation and globalisation are combining to generate a world with a surfeit of labour and too little work
Excerpt:
A new age is dawning. Whether it is a wonderful one or a terrible one remains to be seen. Look around and the signs of dizzying technological progress are difficult to miss. Driverless cars and drones, not long ago the stuff of science fiction, are now oddities that can occasionally be spotted in the wild and which will soon be a commonplace in cities around the world.
From DSC: I don’t see a world without work being good for us in the least. I think we humans need to feel that we are contributing to something. We need a purpose for living out our days here on Earth (even thoughthey are but a vapor). We need vision…goals to works towards as we seek to use the gifts, abilities, passions, and interests that the LORD gave to us. The author of the above article would also add that work:
Is a source of personal identity
It helps give structure to our days and our lives
It offers the possibility of personal fulfillment that comes from being of use to others
Is a critical part of the glue that holds society together and smooths its operation
Over the last generation, work has become ever less effective at performing these roles. That, in turn, has placed pressure on government services and budgets, contributing to a more poisonous and less generous politics. Meanwhile, the march of technological progress continues, adding to the strain.
Immune Engineering
Genetically engineered immune cells are saving the lives of cancer patients. That may be just the start.
Precise Gene Editing in Plants
CRISPR offers an easy, exact way to alter genes to create traits such as disease resistance and drought tolerance.
Conversational Interfaces
Powerful speech technology from China’s leading Internet company makes it much easier to use a smartphone.
Reusable Rockets
Rockets typically are destroyed on their maiden voyage. But now they can make an upright landing and be refueled for another trip, setting the stage for a new era in spaceflight.
Robots That Teach Each Other
What if robots could figure out more things on their own and share that knowledge among themselves?
DNA App Store
An online store for information about your genes will make it cheap and easy to learn more about your health risks and predispositions.
SolarCity’s Gigafactory
A $750 million solar facility in Buffalo will produce a gigawatt of high-efficiency solar panels per year and make the technology far more attractive to homeowners.
Slack
A service built for the era of mobile phones and short text messages is changing the workplace.
Tesla Autopilot
The electric-vehicle maker sent its cars a software update that suddenly made autonomous driving a reality.
Power from the Air
Internet devices powered by Wi-Fi and other telecommunications signals will make small computers and sensors more pervasive
We live in an age of transformative scientific powers, capable of changing the very nature of the human species and radically remaking the planet itself.
Advances in information technologies and artificial intelligence are combining with advances in the biological sciences; including genetics, reproductive technologies, neuroscience, synthetic biology; as well as advances in the physical sciences to create breathtaking synergies — now recognized as the Fourth Industrial Revolution.
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Since these technologies will ultimately decide so much of our future, it is deeply irresponsible not to consider together whether and how to deploy them. Thankfully there is growing global recognition of the need for governance.
This then leads to the ethical implications of using robots. Embracing a number of areas of research, robot ethics considers whether the use of a device within a particular field is acceptable and also whether the device itself is behaving ethically. When it comes to robot babies there are already a number of issues that are apparent. Should “parents” be allowed to choose the features of their robot, for example? How might parents be counseled when returning their robot baby? And will that baby be used again in the same form?
China’s policing robot: Cattle prod meets supercomputer— from computerworld.com by Patrick Thibodeau China’s fastest supercomputers have some clear goals, namely development of its artificial intelligence, robotics industries and military capability, says the U.S.
Late last month, popular websites like Twitter, Pinterest, Reddit and PayPal went down for most of a day. The distributed denial-of-service attack that caused the outages, and the vulnerabilities that made the attack possible, was as much a failure of market and policy as it was of technology. If we want to secure our increasingly computerized and connected world, we need more government involvement in the security of the “Internet of Things” and increased regulation of what are now critical and life-threatening technologies. It’s no longer a question of if, it’s a question of when.
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An additional market failure illustrated by the Dyn attack is that neither the seller nor the buyer of those devices cares about fixing the vulnerability. The owners of those devices don’t care. They wanted a webcam — or thermostat, or refrigerator — with nice features at a good price. Even after they were recruited into this botnet, they still work fine — you can’t even tell they were used in the attack. The sellers of those devices don’t care: They’ve already moved on to selling newer and better models. There is no market solution because the insecurity primarily affects other people. It’s a form of invisible pollution.
CIO’s Sharon Florentine took a look at data from global freelance marketplace Upwork, based on annual job posting growth and skills demand. The following are leading IoT skills Florentine identified that will be demand as the IoT proliferates, with level the growth seen over a one-year period:
Circuit design (231% growth): Builds miniaturized circuit boards for sensors and devices.
Microcontroller programming (225% growth): Writes code that provides intelligence to microcontrollers, the embedded chips within IoT devices.
AutoCAD (216% growth): Designs the devices.
Machine learning (199% growth): Writes the algorithms that recognize data patterns within devices.
Security infrastructure (194% growth): Identifies and integrates the standards, protocols and technologies that protect devices, as well as the data inside.
Big data (183% growth): Data scientists and engineers “who can collect, organize, analyze and architect disparate sources of data.” Hadoop and Apache Spark are two areas with particularly strong demand.
#Blockchain will likely be used by colleges, universities, bootcamps, MOOCs, and others to feed web-based learner profiles, which will then be queried by people and/or organizations who are looking for freelancers and/or employees to fill their project and/or job-related needs.
As of the end of 2016, Microsoft — with their purchase of LinkedIn — is strongly positioned as being a major player in this new landscape. But it might turn out to be an open-sourced solution/database.
Data mining, algorithm development, and Artificial Intelligence (AI) will likely have roles to play here as well. The systems will likely be able to tell us where we need to grow our skillsets, and provide us with modules/courses to take. This is where the Learning from the Living [Class] Room vision becomes highly relevant, on a global scale. We will be forced to continually improve our skillsets as long as we are in the workforce. Lifelong learning is now a must. AI-based recommendation engines should be helpful here — as they will be able to analyze the needs, trends, developments, etc. and present us with some possible choices (based on our learner profiles, interests, and passions).
Alongside a former Stanford researcher—Jia Li, who more recently ran research for the social networking service Snapchat—the China-born Fei-Fei will lead a team inside Google’s cloud computing operation, building online services that any coder or company can use to build their own AI. This new Cloud Machine Learning Group is the latest example of AI not only re-shaping the technology that Google uses, but also changing how the company organizes and operates its business.
Google is not alone in this rapid re-orientation.Amazon is building a similar group cloud computing group for AI. Facebook and Twitter have created internal groups akin to Google Brain, the team responsible for infusing the search giant’s own tech with AI. And in recent weeks, Microsoft reorganized much of its operation around its existing machine learning work, creating a new AI and research group under executive vice president Harry Shum, who began his career as a computer vision researcher.
But Etzioni says this is also part of very real shift inside these companies, with AI poised to play an increasingly large role in our future. “This isn’t just window dressing,” he says.
AI and Advanced Machine Learning
Artificial intelligence (AI) and advanced machine learning (ML) are composed of many technologies and techniques (e.g., deep learning, neural networks, natural-language processing [NLP]). The more advanced techniques move beyond traditional rule-based algorithms to create systems that understand, learn, predict, adapt and potentially operate autonomously. This is what makes smart machines appear “intelligent.”
“Applied AI and advanced machine learning give rise to a spectrum of intelligent implementations, including physical devices (robots, autonomous vehicles, consumer electronics) as well as apps and services (virtual personal assistants [VPAs], smart advisors), ” said David Cearley, vice president and Gartner Fellow. “These implementations will be delivered as a new class of obviously intelligent apps and things as well as provide embedded intelligence for a wide range of mesh devices and existing software and service solutions.”
Google is letting users peek into some of its most experimental artificial intelligence projects.
The company unveiled a new website Tuesday called A.I. Experiments that showcases Google’s artificial intelligence research through web apps that anyone can test out. The projects include a game that guesses what you’re drawing, a camera app that recognizes objects you put in front of it and a music app that plays “duets” with you.
On Tuesday, Google Cloud chief Diane Greene announced the formation of a new team, the Google Cloud Machine Learning group, that will manage the Mountain View, California-based company’s cloud intelligence efforts going forward.
In 10 years, Google Translate has gone from supporting just a few languages to 103, connecting strangers, reaching across language barriers and even helping people find love. At the start, we pioneered large-scale statistical machine translation, which uses statistical models to translate text. Today, we’re introducing the next step in making Google Translate even better: Neural Machine Translation.
Neural Machine Translation has been generating exciting research results for a few years and in September, our researchers announced Google’s version of this technique. At a high level, the Neural system translates whole sentences at a time, rather than just piece by piece. It uses this broader context to help it figure out the most relevant translation, which it then rearranges and adjusts to be more like a human speaking with proper grammar. Since it’s easier to understand each sentence, translated paragraphs and articles are a lot smoother and easier to read. And this is all possible because of end-to-end learning system built on Neural Machine Translation, which basically means that the system learns over time to create better, more natural translations.
‘Augmented Intelligence’ for Higher Ed — from insidehighered.com by Carl Straumsheim IBM picks Blackboard and Pearson to bring the technology behind the Watson computer to colleges and universities.
Excerpts:
[IBM] is partnering with a small number of hardware and software providers to bring the same technology that won a special edition of the game show back in 2011 to K-12 institutions, colleges and continuing education providers. The partnerships and the products that might emerge from them are still in the planning stage, but the company is investing in the idea that cognitive computing — natural language processing, informational retrieval and other functions similar to the ones performed by the human brain — can help students succeed in and outside the classroom.
Chalapathy Neti, vice president of education innovation at IBM Watson, said education is undergoing the same “digital transformation” seen in the finance and health care sectors, in which more and more content is being delivered digitally.
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IBM is steering clear of referring to its technology as “artificial intelligence,” however, as some may interpret it as replacing what humans already do.
“This is about augmenting human intelligence,” Neti said. “We never want to see these data-based systems as primary decision makers, but we want to provide them as decision assistance for a human decision maker that is an expert in conducting that process.”
The combination of machine learning, deep learning, natural language processing, and cognitive computing will soon change the ways that we interact with our environments. AI-driven smart services will sense what we’re doing, know what our preferences are from our past behavior, and subtly guide us through our daily lives in ways that will feel truly seamless.
Perhaps the best way to explore how such systems might work is by looking at an example: a visit to a hospital.
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The AI loop includes seven steps:
Perception describes what’s happening now.
Notification tells you what you asked to know.
Suggestion recommends action.
Automation repeats what you always want.
Prediction informs you of what to expect.
Prevention helps you avoid bad outcomes.
Situational awareness tells you what you need to know right now.
Since 2011, Japan’s National Institute of Informatics has been working on an AI, with the end goal of having it pass the entrance exam for the University of Tokyo, according to a report from Engadget. This endeavor, dubbed the Todai Robot Project in reference to a local nickname for the school, has been abandoned.
It turns out that the AI simply cannot meet the exact requirements of the University of Tokyo. The team does not expect to reach their goal of passing the test by March 2022, so the project is being brought to an end.
“We are building not just Azure to have rich compute capability, but we are, in fact, building the world’s first AI supercomputer,” he said.
As artificial intelligence and machine learning mature and manifest their potential to take on complicated tasks, we’ve become somewhat expectant that robots can succeed where humans have failed — namely, in putting aside personal biases when making decisions. But as recent cases have shown, like all disruptive technologies, machine learning introduces its own set of unexpected challenges and sometimes yields results that are wrong, unsavory, offensive and not aligned with the moral and ethical standards of human society.
While some of these stories might sound amusing, they do lead us to ponder the implications of a future where robots and artificial intelligence take on more critical responsibilities and will have to be held responsible for the possibly wrong decisions they make.
This list is a primer for non-technical people who want to understand what machine learning makes possible.
To develop a deep understanding of the space, reading won’t be enough. You need to: have an understanding of the entire landscape, spot and use ML-enabled products in your daily life (Spotify recommendations), discuss artificial intelligence more regularly, and make friends with people who know more than you do about AI and ML.
News: For starters, I’ve included a link to a weekly artificial intelligence email that Avi Eisenberger and I curate (machinelearnings.co). Start here if you want to develop a better understanding of the space, but don’t have the time to actively hunt for machine learning and artificial intelligence news.
Startups: It’s nice to see what startups are doing, and not only hear about the money they are raising. I’ve included links to the websites and apps of 307+ machine intelligence companies and tools.
People: Here’s a good place to jump into the conversation. I’ve provided links to Twitter accounts (and LinkedIn profiles and personal websites in their absence) of the founders, investors, writers, operators and researchers who work in and around the machine learning space.
Events: If you enjoy getting out from behind your computer, and want to meet awesome people who are interested in artificial intelligence in real life, there is one place that’s best to do that, more on my favorite place below.
When we think about artificial intelligence, we often imagine robots performing tasks on the warehouse or factory floor that were once exclusively the work of people. This conjures up the specter of lost jobs and upheaval for many workers. Yet, it can also seem a bit remote — something that will happen in “the future.” But the future is a lot closer than many realize. It also looks more promising than many have predicted.
Stitch Fix provides a glimpse of how some businesses are already making use of AI-based machine learning to partner with employees for more-effective solutions. A five-year-old online clothing retailer, its success in this area reveals how AI and people can work together, with each side focused on its unique strengths.
Excerpt (emphasis DSC):
As the White House report rightly observes, the implications of an AI-suffused world are enormous — especially for the people who work at jobs that soon will be outsourced to artificially-intelligent machines. Although the report predicts that AI ultimately will expand the U.S. economy, it also notes that “Because AI has the potential to eliminate or drive down wages of some jobs … AI-driven automation will increase the wage gap between less-educated and more-educated workers, potentially increasing economic inequality.”
Accordingly, the ability of people to access higher education continuously throughout their working lives will become increasingly important as the AI revolution takes hold. To be sure, college has always helped safeguard people from economic dislocations caused by technological change. But this time is different. First, the quality of AI is improving rapidly. On a widely-used image recognition test, for instance, the best AI result went from a 26 percent error rate in 2011 to a 3.5 percent error rate in 2015 — even better than the 5 percent human error rate.
Moreover, as the administration’s report documents, AI has already found new applications in so-called “knowledge economy” fields, such as medical diagnosis, education and scientific research. Consequently, as artificially intelligent systems come to be used in more white-collar, professional domains, even people who are highly educated by today’s standards may find their livelihoods continuously at risk by an ever-expanding cybernetic workforce.
As a result, it’s time to stop thinking of higher education as an experience that people take part in once during their young lives — or even several times as they advance up the professional ladder — and begin thinking of it as a platform for lifelong learning.
Colleges and universities need to be doing more to move beyond the array of two-year, four-year, and graduate degrees that most offer, and toward a more customizable system that enables learners to access the learning they need when they need it. This will be critical as more people seek to return to higher education repeatedly during their careers, compelled by the imperative to stay ahead of relentless technological change.
From DSC: That last bolded paragraph is why I think the vision of easily accessible learning — using the devices that will likely be found in one’s apartment or home — will be enormously powerful and widespread in a few years. Given the exponential pace of change that we are experiencing — and will likely continue to experience for some time — people will need to reinvent themselves quickly.
Higher education needs to rethink our offerings…or someone else will.
SAN FRANCISCO, Nov. 9, 2016 /PRNewswire/ — IBM (NYSE: IBM) today unveiled the experimental release of Project Intu, a new, system-agnostic platform designed to enable embodied cognition. The new platform allows developers to embed Watson functions into various end-user device form factors, offering a next generation architecture for building cognitive-enabled experiences.
Project Intu, in its experimental form, is now accessible via the Watson Developer Cloud and also available on Intu Gateway and GitHub.
SAN FRANCISCO, Nov. 9, 2016 /PRNewswire/ — At the IBM (NYSE: IBM) Watson Developer Conference, IBM announced a partnership with Topcoder, the premier global software development community comprised of more than one million designers, developers, data scientists, and competitive programmers, to advance learning opportunities for cognitive developers who are looking to harness the power of Watson to create the next generation of artificial intelligence apps, APIs, and solutions. This partnership also benefits businesses that gain access to an increased talent pool of developers through the Topcoder Marketplace with experience in cognitive computing and Watson.
5 Ways Artificial Intelligence Is Shaping the Future of E-commerce — from entrepreneur.com by Sheila Eugenio Paradoxically for a machine, AI’s greatest strength may be in creating a more personal experience for your customer. From product personalization to virtual personal shoppers.
Excerpt:
Here are three ways AI will impact e-commerce in the coming years:
Getting kids interested in STEM subjects is an ongoing challenge, and Teacher Advisor with Watson, a free tool, will help elementary school teachers match materials with student needs. In its first phase, it’s being used by 200 teachers, assisting them in creating math lessons that engage students and help them learn. The plan is to roll it out to all U.S. elementary schools by year end. As time goes on, Watson will learn from teacher feedback and improve its recommendations. There is, Rometty said, an opportunity to also build in professional development resources.
Even professional lip-readers can figure out only 20% to 60% of what a person is saying. Slight movements of a person’s lips at the speed of natural speech are immensely difficult to reliably understand, especially from a distance or if the lips are obscured. And lip-reading isn’t just a plot point in NCIS: It’s an essential tool to understand the world for the hearing-impaired, and if automated reliably, could help millions.
A new paper (pdf) from the University of Oxford (with funding from Alphabet’s DeepMind) details an artificial intelligence system, called LipNet, that watches video of a person speaking and matches text to the movement of their mouth with 93.4% accuracy.
In the first few months of the new semester hubbub, what if there was an assistant at the beck and call of students to help them navigate the college process? While the campus faculty and staff are likely too busy during those first few days to answer all the questions on students and parent’s minds, chatbots – akin to Siri, Cortana, and Alexa – could provide the ideal digital assistant to make not only these first few days run smoothly, but also the student’s entire time on campus.
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From applying to college, to arriving on campus, declaring a major, signing up courses and eventually graduation, there are a multitude of ways bots can help to streamline the process, maybe as soon as next semester.
… For example, during the application process, a bot could send push notifications to students to remind them about upcoming deadlines, missing documents, or improperly submitted data, and would be available 24/7 to answer student’s questions such as “Am I missing any documents for my application?” or “What’s the deadline for submitting the application fee?”.
The incredible potential of chatbots lies in the ability to individually and contextually communicate one-to-many.
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Right now contextually communicating with bots isn’t something that’s reasonable to ask across the board but there are a few that are doing it well, and I believe this type of interaction will be the standard in the future.
While chatbots are still in their infancy in terms of creative potential, it’s still a very exciting time for creatives trying to understand the best way to use this new technology and how to build the best bot possible.
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Stop wasting money trying to pull people into your ecosystem. Push your content where your users are already active.
Developers and the rest of the world will soon be able to make bots that interact with Google Assistant and new Google devices made public, the company said today in a special presentation in San Francisco.
“The Google Assistant will be our next thriving open ecosystem,” said Scott Huffman, lead engineer of Google Assistant.
The creation of bots for Google Assistant will be possible through Actions on Google, which is due out by early December. A software development kit (SDK) that brings Google Assistant into a range of device not made by Google is due out next year.
Bots are applications that are designed to respond to conversational language. The aim is to create services — whether that’s the ability to order a pizza or to enter a meeting in a calendar — where the dialogue with the app is as natural and apparently unscripted as an interaction you might have with a human.
Chat bots are like narrow versions of digital assistants like Apple’s Siri, Amazon’s Alexa or Google Assistant, designed to perform specific tasks. Interest in bots has rocketed recently and developers are racing to incorporate them into services built on popular messaging apps and websites to create a form of virtual customer services.
Dear Francesca, Eric, Mustafa, Yann, Ralf, Demis and others at IBM, Microsoft, Google, Facebook and Amazon.
The Partnership on AI to benefit people and society is a welcome change from the usual celebration of disruption and magic technological progress. I hope it will also usher in a more holistic discussion about the global ethics of the digital age. Your announcement also coincides with the launch of my book Technology vs. Humanity which dramatises this very same question: How will technology stay beneficial to society?
This open letter is my modest contribution to the unfolding of this new partnership. Data is the new oil – which now makes your companies the most powerful entities on the globe, way beyond oil companies and banks. The rise of ‘AI everywhere’ is certain to only accelerate this trend. Yet unlike the giants of the fossil-fuel era, there is little oversight on what exactly you can and will do with this new data-oil, and what rules you’ll need to follow once you have built that AI-in-the-sky. There appears to be very little public stewardship, while accepting responsibility for the consequences of your inventions is rather slow in surfacing.
![The Living [Class] Room -- by Daniel Christian -- July 2012 -- a second device used in conjunction with a Smart/Connected TV](http://danielschristian.com/learning-ecosystems/wp-content/uploads/2012/07/The-Living-Class-Room-Daniel-S-Christian-July-2012.jpg)
