Category Archives: Ai

Facebook has started deploying its artificial intelligence capabilities to help combat terrorists' use of its service.

Company officials said in a blog post Thursday that Facebook will use AI in conjunction with human reviewers to find and remove "terrorist content" immediately, before other users see it. Such technology is already used to block child pornography from Facebook and other services such as YouTube, but Facebook had been reluctant about applying it to other potentially less clear-cut uses.

In most cases, Facebook only removes objectionable material if users first report it.

Facebook and other internet companies face growing government pressure to identify and prevent the spread of terrorist propaganda and recruiting messages on their services. Earlier this month, British Prime Minister Theresa May called on governments to form international agreements to prevent the spread of extremism online. Some proposed measures would hold companies legally accountable for the material posted on their sites.

The Facebook post by Monika Bickert, director of global policy management, and Brian Fishman, counterterrorism policy manager did not specifically mention May's calls. But it acknowledged that "in the wake of recent terror attacks, people have questioned the role of tech companies in fighting terrorism online."

"We want to answer those questions head on. We agree with those who say that social media should not be a place where terrorists have a voice," they wrote.

Among the AI techniques used in this effort are image matching, which compares photos and videos people upload to Facebook to "known" terrorism images or video. Matches generally mean that either that Facebook had previously removed that material, or that it had ended up in a database of such images that Facebook shares with Microsoft, Twitter and YouTube.

Facebook is also developing "text-based signals" from previously removed posts that praised or supported terrorist organizations. It will feed those signals into a machine-learning system, over time, will learn how to detect similar posts.

Bickert and Fishman said that when Facebook receives reports of potential "terrorism posts," it reviews those reports urgently. In addition, it says that in the rare cases when it uncovers evidence of imminent harm, it promptly informs authorities.

But AI is just part of the process. The technology is not yet at the point where it can understand nuances of language and context, so humans are still in the loop.

Facebook says it employs more than 150 people who are "exclusively or primarily focused on countering terrorism as their core responsibility." This includes academic experts on counterterrorism, former prosecutors, former law enforcement agents and analysts and engineers, according to the blog post.

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Facebook deploys AI to fight terrorism on its network - ABC News

Disruption is inevitable, but also deeply feared. Weve seen this with every significant technological leap -- from the printing press to automobiles to computers. But, as we enter the next iteration of technology with AI, we know it will have a profound, transformative effect on global business and society. However, we must reflect on how we want this transformation to occur.

Early adoption has already begun: AI is transforming everyday activities and processes such as virtual assistants, fraud detection and driverless cars. Various forms of AI solutions are already in the market, including automation, speech recognition, machine learning, decision-making and natural language processing. Organizations that are already investing in these technologies are better positioned for long-term success.

Related: Why Small Business Should Be Paying Attention to Artificial Intelligence

As a society, we must accept the fact that AI is here to stay, and realize thoughtful adoption of the technology is critical.

But, what does this mean for the workforce? For software developers, data scientists, engineers and the full spectrum of information technology workers, AI is perceived to either be putting their jobs at risk, or changing their responsibilities to accommodate its rapid advancement. While its difficult to predict the pace of AI adoption, some of the technologys most influential leaders and early adopters agree that its advancing faster than anticipated. As AIs development accelerates and implementations spread, it raises the question for workers in tech and other industries: Are my skills still relevant?

A positive, counterintuitive side effect of early AI adoption is that its requiring companies to invest in their employees. Bringing AI into the enterprise calls for investments in software and technologies that support its implementation, but also in the training and skill building for employees working alongside it. Companies cant go all-in on AI without balancing the investment ratio between technology and human workers.

Recentresearchby Infosys revealed that globally, 76 percent of decision makers agree AI is fundamental to the success of their organizations strategy. More optimistically, 80 percent of respondents say theyll retrain or redeploy employees whose roles are replaced or plan to be replaced with new technologies. This is why its essential to rethink our approach to education and employee development and lay a foundation for continuous lifelong learning.

Related: How to Learn Anything in the Age of AI

This shift in learning is necessary not only for the workforce today, but for future generations. We are developing and deploying AI systems that will become so advanced they will become part of the fabric of every industry. Students, academics and workers will need the skills and expertise to work intimately with AI systems. This new mentality requires a curious mindset and a thirst for knowledge and learning.

Decades from now, AI may replace cognitive tasks such as identifying and solving problems. Today, AI can identify patterns and anomalies in environments and production and notify humans about that information, which may not have been uncovered otherwise. However, human creativity and ingenuity will always be required tofindthe problems AI can solve in the first place.

After all, humans do not simply endure technological disruption -- they help shape it as part of our future. The advent of the automobile didnt just help us travel faster and further; rather, it led to roads, highways and entirely new industries.

Similarly, AI can be a great enabling force that amplifies and empowers people, improves the quality of life for all and opens up opportunities for the underprivileged. Its not a question of man versus machine, but manandmachine.

Related: Will a Robot Take My Job?

Providing employees with the opportunity to pursue learning and training programs to enhance their careers and help them understand new AI applications benefits employers as well. It encourages a more knowledgeable workforce thats inspired and motivated. It also creates the type of employees that become problem-finders seeking out the unknown unknowns, and begin the work of turning these problems into solutions. Increasingly, this will involve the aid of AI.

To reach the full human potential offered by AI, education and training must be a priority. For this to happen, digitalliteracy is fundamental for every future generation. Each child must have access to computer science courses. But, doing this requires a new perspective on education by both government and the private sector -- otherwise the education and skill sets of employees now and in the future wont rise to meet the rapid adoption of AI.

This also means rethinking education, recasting it as a life-long process,and deemphasizing rewarding memorization and routine in favor of curiosity and experimentation. We must modernize courses to encourage creative problem finding and solving, and learning through doing, with mandatory computer science learning as the bedrock for enabling digital literacy. Organizations also need to make life-long learning resources available for employees to enhance skills development and can dedicate a percentage of their annual revenue to reskilling staff.

Its a pivotal point in human history. AI is under construction before our eyes as the next great technological evolution, and we must be prepared to evolve alongside it.

Abdul Razack heads the Platforms Group at Infosys, focusing on overseeing platforms and reusable components across services, Big Data, automation, and the analytics business. Prior to Infosys, he worked at SAP, as senior vice president for...

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How to Prepare Employees to Work With AI - Entrepreneur

Microsoft Corp. (MSFT), NVIDIA Corp. (NVDA) and Intel Corp. (INTC) all participated in a round of fund raising for Element AI, the Canadian artificial intelligence startup, as the technology powerhouses go after the burgeoning market.

According to media reports, Microsoft made the investment via its venture capital arm Microsoft Ventures, while Intel did it via Intel Capital. The startup that developed a platform to help companies of all sizes build AI into their businesses, raised $102 million. The Series A round of funding was led by Data Collective, a San Francisco VC firm. Microsoft is a previous investor in Element AI, which splashed onto the scene just a mere eight months ago.

Element AI told ZDNet that it will use the funding to hire more employees, to invest in big AI projects and to acquire startups in the space. "Artificial Intelligence is a 'must have' capability for global companies," said CEO Jean-Franois Gagn in a statement. "Without it, they are competitively impaired if not at grave risk of being obsoleted in place."

For the Redmond, Wash., software giant, Element AI marks yet another instance where it recently backed a company focused on this new technology. In May it co-led a $7.6 million VC round of funding for Bonsai, the Berkeley, Calif.-based AI startup, and invested in Agolo, a New York City-based AI startup. Bonsais AI technology is designed to help manufacturing, retail, logistic and similar markets incorporate AI into their businesses. Agolo provides AI systems to some of the worlds biggest media companies to summarize their news on Facebook and via Amazons Alexa, voice-activated personal assistant. (See also: Sports Betting: The Next Big Thing for Artificial Intelligence.)

But its not just Microsoft that is setting its sights on the market. Chipmaker NVIDIA is also becoming a force, which has prompted Citigroup to predict the stock could hit $300 a share. In a recent research note, Citi analyst Atif Malik said the company is in the early stages of transitioning from a maker of PC graphics chips to a leader in AI, which could drive future growth.

"Element AI will benefit by continuing to leverage NVIDIA's high performance GPUs and software at large scale to solve some of the world's most challenging issues," Jeff Herbst, VP of business development at NVIDIA, said in a statement to ZDNet about its participation in the round of fundraising. Meanwhile Intel recently announced it is forming a separate AI business unit that will be led by former Nervana CEO Naveen Rao. (See also: Intel Forms New Unit to Zero in on AI.)

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Microsoft, Intel, NVIDIA Invest in Element AI - Investopedia

Mac Rumors

Microsoft Pix can now turn your iPhone photos into art, thanks to ... TechCrunch Microsoft is rolling out an update to its AI-powered photo editing app, Microsoft Pix, that aims to give Prisma and others like it some new competition. While.. Microsoft Updates iOS Photo App 'Pix' With Artistic Filters Powered ...Mac Rumors all 7 news articles »

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Microsoft Pix can now turn your iPhone photos into art, thanks to ... - TechCrunch

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TechCrunch

Conviva nabs $40M for AI-based video analytics, now valued ... TechCrunch As more video providers finding audiences directly through apps and the web and away from pay-TV-based packages we're seeing the emergence of ... and more »

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Conviva nabs $40M for AI-based video analytics, now valued ... - TechCrunch

The maximum score possible.

It's official. Humans are now second-best at playing Ms. Pac-Man, a 1980s twist on the arcade classic, involving eating pellets and being chased by ghosts. It was rated as one of the hardest games for an AI to beat, but that didn't stop one.

An AI from Microsoft's Maluuba team -- a Canadian deep learning startup the company acquired earlier this year --has now scored the maximum score possible of 999,990 in the Atari game, beating the human record by four times.

This was achieved using a method of reinforcement learning called Hybrid Reward Architecture. The team taught 150 AI agents to work together in parallel to master the game. Agents were rewarded for eating pellets while other agents avoided ghosts. A top agent then got feedback from the others and used a weighted average to make decisions.

It's not just Microsoft's AI that's in the business of beating humans at games. Google's champion game-playing artificial intelligence program called AlphaGo defeated one of the top Go (an ancient Chinese board game) masters last year, Lee Se-dol. This year, it defeated current Go champion Ke Jie.

Microsoft's AI's success at an unpredictable game could see researchers help AI tackle equally unpredictable real-world situations.

Special Reports: CNET's in-depth features in one place.

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Microsoft AI gets maximum score possible on Ms. Pac-Man - CNET

If AI and robots are going to take our jobs, at least they can do it in the most relaxing way possible. Just like Shimon here a four-armed marimba-playing robot designed by George Techs music technology center. Sure, Shimon is just the tip of the iceberg when it comes to AI making music, but just listen to those jazz-fusion vibes.

Like many AI music experiments, the music Shimon is playing is generated by a method called deep learning. This essentially means mining a large amount of information (in this case, a dataset of some 5,000 songs) and looking for common patterns in the music. For example, if you have a sequence of notes F, G, A, what note will follow next? Deep learning will give you a good answer.

Shimon the robot has been around for a while now, playing alongside human musicians using pre-programmed songs. But now, its being used to play original compositions. The video above shows the first melody Shimon ever created, while the one below is melody number two a slightly faster number:

As weve seen with previous experiments, the actual musical output is a bit avante garde. Researchers working in this field say this is because the deep learning systems we use to analyze music tend not to be so good at thinking about long-term structure. They analyze the music in short bursts, and the resulting melodies sound quite abstract. It is possible to program in artificial constraints so the programs will produce songs with traditional verse-chorus structures, but at that point its not really AI-created music, but AI-human collaboration.

So, although the marimba is a particularly non-threatening instrument, the melody itself is proof that machines have a way to go. For more information on Shimon, check out this interview with its teachers, Gil Weinberg and Mason Bretan, over at IEEE Spectrum.

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This AI-powered robot can play the marimba, the least threatening of instruments - The Verge

Facebook is teaching chat bots a new skill.

One day, the art of the deal might just involve lettingartificial intelligencedo your dirty work for you.

Researchers from Facebook Artificial Intelligence Research (FAIR) have created AI models, or what they call dialog agents, that can negotiate, according to a blog post Wednesday. They're publishing open-source code as well as research on those dialog agents, the result of about six months' work on the project.

The idea is that negotiation is a basic part of life whether you're picking a restaurant with friends or deciding on a movie to watch. But current chat bots aren't capable of much complexity. Their state of the art is to do simple tasks like book a restaurant or have short conversations of limited scope.

FAIR worked on the problem of how to get dialog agents to operate like people -- that is, come into a situation with different goals and eventually reach a compromise.

The effort is part of a broader push by Facebook to get us to use chat bots. At its developer conference in 2016, founder and CEO Mark Zuckerberg walked through scenarios in which you might use a bot to interact with a business, for example, to order a product or get customer service help. While tech giants like Facebook, Google and Apple are keen to build the personal digital assistant of the future, today's helpers still lack the necessary skills.

It's just one stitch in the larger fabric of work by Silicon Valley, academic researchers and the business community in the area of artificial intelligence, driven by powerful chips, fast networks and access to massive amounts of data about how people lead their digital lives. That's showing up in everything from sorting photos on Facebook to beating Go champions and diagnosing medical conditions.

FAIR didn't delve too far into what applications might be appropriate for bot-bargaining or whether this capability will surface in any Facebook products. But the post did mention this could be an advantage for bot developers working on chat bots with the ability to "reason, converse and negotiate, all key steps toward building a personalized digital assistant."

Negotiation, the FAIR post explains, is both a linguistic and reasoning problem. In other words, you've got to know what you want several steps down the road and be able to communicate it.

In one example, dialog agents were tasked with dividing up a collection of items like five books, three hats and two balls. Each agent had different priorities and each item carried a different value for each agent. The AIs were taught, in a sense, that walking away from the negotiation wasn't an option.

The ability to think ahead is crucial and with the introduction of something called dialog rollouts, which simulate future conversations, the bots were able to do so.

Or as FAIR scientist Mike Lewis put it: "If I say this, you might say that, and then I'll say something else." Lewis said those rollouts are the key innovation in this project.

The research has boosted performance in using various negotiation tactics, like being able to negotiate until there's a successful outcome, propose more final deals and produce novel sentences. The agents even started pretending to be interested in an item so they could later concede it as if it were a compromise.

Humans had a chance to try out the agents, and the researchers said the people couldn't tell they were chatting with bots.

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Outfoxed by a bot? Facebook is teaching AI to negotiate - CNET

AI isnt going to be a threat to humanity because its evil or cruel, AI will be a threat to humanity because we havent properly explained what it is we want it to do. Consider the classic paperclip maximizer thought experiment, in which an all-powerful AI is told, simply, make paperclips. The AI, not constrained by any human morality or reason, does so, eventually transforming all resources on Earth into paperclips, and wiping out our species in the process. As with any relationship, when talking to our computers, communication is key.

Thats why a new piece of research published yesterday by Googles DeepMind and the Elon Musk-funded OpenAI institute is so interesting. It offers a simple way for humans to give feedback to AI systems crucially, without the instructor needing to know anything about programming or artificial intelligence.

The method is a variation of whats known as reinforcement learning or RL. With RL systems, a computer learns by trial-and-error, repeating the same task over and over, while programmers direct its actions by setting certain reward criteria. For example, if you want a computer to learn how to play Atari games (something DeepMind has done in the past) you might make the games point system the reward criteria. Over time, the algorithm will learn to play in a way that best accrues points, often leading to super-human performance.

What DeepMind and OpenAIs researchers have done is replace this predefined reward criteria with a much simpler feedback system. Humans are shown an AI performing two versions of the same task and simply tell it which is better. This happens again and again, and eventually the systems learns what is expected of it. Think of it like getting an eye test, when youre looking through different lenses, and being asked over and over: better... or worse? Heres what that looks like when teaching a computer to play the classic Atari game Q*bert:

This method of feedback is surprisingly effective, and researchers were able to use it to train an AI to play a number of Atari video games, as well perform simulated robot tasks (like picking telling an arm to pick up a ball). This better / worse reward function could even be used to program trickier behavior, like teaching a very basic virtual robot how to backflip. Thats how we get to the GIF at the top of the page. The behavior you see has been created by watching the Hopper bot jump up and down, and telling it well done when it gets a bit closer to doing a backflip. Over time, it learns how.

Of course, no one is suggesting this method is a cure-all for teaching AI. There are a number of big downsides and limitations in using this sort of feedback. The first being that although it doesnt take much skill on behalf of the human operator, it does take time. For example, in teaching the Hopper bot to backflip, a human was asked to judge its behavior some 900 times a process that took about an hour. The bot itself had to work through 70 hours of simulated training time, which was sped up artificially.

For some simple tasks, says Oxford Robotics researcher Markus Wulfmeier (who was not involved in this research), it would be quicker for a programmer to simply define what it is they wanted. But, says Wulfmeier, its increasingly important to render human supervision more effective for AI systems, and this paper represents a small step in the right direction.

DeepMind and OpenAI say pretty much the same its a small step, but a promising one, and in the future, theyre looking to apply it to more and more complex scenarios. Speaking to The Verge over email, DeepMind researcher Jan Leike said: The setup described in [our paper] already scales from robotic simulations to more complex Atari games, which suggests that the system will scale further. Leike suggests the next step is to test it in more varied 3D environments. You can read the full paper describing the work here.

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This backflipping noodle has a lot to teach us about AI safety - The Verge