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The room where it happened was decked out like a faux studya place where a couple of friends might engage in a friendly game of chess. But the people at the chessboard were professionals, and only one was paid to play chess. One was IBM computer scientist Murray Campbell, whose job it was to move pieces at the instructions of a computer he helped program. He sat with an air of detachment mixed with anticipation, like a passenger on public transit not sure where the bus will stop. The other was world champion chess player Garry Kasparov, whose concentration was intense enough to start a fire in a rainforest. His head hovered over the chessboard as if trying to identify which piece was threatening to betray him. His ankles shook. He was clearly under epic stress. Meanwhile, his putative opponent a supercomputer housed elsewhere on the 35th floor of this midtown skyscrapernot only did not suffer stress, but did not even know what stress was.

I was in that room, for a few minutes at least, taking a turn at occupying one of its eight seats. It was February 1997, and I was covering the Kasparov-Deep Blue matchthe historic contest where IBMs computer would beat the world championfor Newsweek. In my own tribes form of jousting, I had campaigned for the cover, despite the editors declaration that we will never run a cover about chess. I successfully argued that this was not about a game of chess, but rather about a much more epic contest between human and artificial intelligence. What clinched it was the cover line I suggested: The Brains Last Stand. It also helped that no celebrity died that week. So it was that Kasparovs X-ray eyes and ultra-confident visage graced the newsstands of America, at a time when people actually paused at the newsstands to see what the weeklies put on their covers. And that Brains Last Stand line would come to be be invoked to this day. Even Kasparov, in a TED Talk last month, cited it twice.

I stand behind that provocation. Even though chess isnt the toughest thing that computers will tackle for centuries, it stood as a handy symbol for human intelligence. No matter what human-like feat computers perform in the future, the Deep Blue match demands an indelible dot on all timelines of AI progress.

But thats not the only reason why that six-game match in the Equitable Center is still so important. Two decades later, its clear that the significance of that outcome rests as much on how Kasparov was defeated. Though brute force computation and clever algorithms had created the winning positions against him, the champion was shattered by a well-planned psychological attack against him, executed by an IBM effort that leveraged its silicon advantages with human cunning. By the final session of the six-game matchone which began with the two opponents tied in pointsKasparov was a haunted ghost of himself. I knew I didnt have the energy for a complex flight, he writes in his recent book, Deep Thinking, explaining why, early in the game, he made a risky move that effectively ended his chances for winning. The machine had gotten inside the humans head.

And therein lies a parable.

Nine weeks or so before the match, I had lunch with Kasparov and C.J. Tan, the IBM scientist who managed the Deep Blue team. Both of those men maintained a veneer of cordiality that occasionally slipped to reveal the high stakes for each. Looking over the transcript 20 years later, a few things jump out at me. One was the confidence of each man. Tan had earlier remarked to a reporter that IBM was not conducting a scientific experiment anymore, and now he amended that to say, Its part of the experiment to how far the computer will go, and were doing everything we can to win. Kasparov was annoyed that the prospect of an IBM victory was even mentioned. I dont think its an appropriate thing to discuss the situation if I lose, said Kasparov. I never lost in my life.

The other interesting point was our discussion about the psychological aspects of the game. I hope it will be as small as possible, said Kasparov.

Today, those aspects seem to loom larger than the technological achievement of Deep Blue. It turns out that Tans remark about IBM doing everything it could to win included waging psychological warfare against its human opponent.

One tool was the element of surprise. Going into the match, Kasparov was frustrated that IBM had not shared printouts of Deep Blues practice games. He felt at a disadvantage because in a contest with any human, he would have a long history of match performance and would be able to tailor a strategy against that persons tendencies and weaknesses. The best he could do against Deep Blue was to study the chess minds who helped IBM program its systembut the only grandmaster on staff was the American player Joel Benjamin, who was not top-ranked, and to Kasparov, not even worth researching. I have better things to do in my life than study Benjamins games, Kasparov told me. But he did suspect that IBM was secretly working with more experienced grandmasters. I asked Tan directly at our lunch if this was so, and the IBM-er replied, No. Only Benjamin.

But at the match, IBM revealed that formidable grandmaster Miguel Illescas was on its team, as well as two other grandmasters who were working in consulting roles. (In his book, Kasparov says he had known only that Illescas had played training matches against Deep Blue.) Kasparov had no way to prepare, and he was thrown off balance.

That was far from the only trick that IBM would use. Heres a small example Kasparov cites in his book. During a match, human players sometimes will play games with the timing of a move. For instance, they might have a firm plan in mind, and if its going their way, instead of making the next move in the cascade right away they might let some time tick off the clock, to feign uncertainty. IBM actually programmed in the equivalent. In a 2009 interview with a chess publication, Illescas revealed that sometimes when Deep Blue instantly knew its next move, it would wait minutes before acting. When a chess computer stalls like this, it typically signals that the machine is having difficulty, or even has crashed. When Kasparov made his best move, the machine would play immediately, trying to give Kasparov the impression he had fallen into a trap. This has a psychological impact as the machine becomes unpredictable, which was our main goal, said Illescas.

The turning point of the match came in Game Two. Kasparov had won the first game and was feeling pretty good. In the second, the match was close and hard fought. But on the 36th move, the computer did something that shook Kasparov to his bones. In a situation where virtually every top-level chess program would have attacked Kasparovs exposed queen, Deep Blue made a much subtler and ultimately more effective move that shattered Kasparovs image of what a computer was capable of doing. It seemed to Kasparovand frankly, to a lot of observers as wellthat Deep Blue had suddenly stopped playing like a computer (by resisting the catnip of the queen attack) and instead adopted a strategy that only the wisest human master might attempt. By underplaying Deep Blues capabilities to Kasparov, IBM had tricked the human into underestimating it. A few days later, he described it this way: Suddenly [Deep Blue] played like a god for one moment. From that moment Kasparov had no idea whator whohe was playing against. In what he described as a fatalistic depression, he played on, and wound up resigning the game.

After Game Two, Kasparov was not only agitated by his loss but also suspicious at how the computer had made a move that was soun-computer like. It made me question everything, he now writes. Getting the printouts that explained what the computer didand proving that there was no human interventionbecame an obsession for him. Before Game Five, in fact, he implied that he would not show up to play unless IBM submitted printouts, at least to a neutral party who could check that everything was kosher. IBM gave a small piece to a third party, but never shared the complete file.

Kasparov was not the same player after Game Two. He fought to draws in the next three games, but in addition to the added mental pressures of dealing with what he clearly believed was his opponents skullduggery, he was physically wearing down. Though both sides were tied going into the final match, Kasparov approached it with dread. Asked in the press conference after Game Five about a comment Illescas made that he was now afraid of Deep Blue, Kasparov said, Im not afraid to admit Im afraid! Quite a difference from his pre-match confidence.

Indeed, Game Six was a debacle. From where we journalists were sitting, Kasparov seemed disengaged from the start. Afterwards, he claimed that he wasnt in the mood of playing at all. On his seventh move, on what should have been a routine opening-game move, he made a mistake so egregiously awful that there were cries of disbelief in the auditorium where spectators were gathered. It was almost like he was throwing the game. He played in a desultory fashion for a few moves, and then resigned in obvious disgust. In a chaotic post-game press conference, Kasparov alternated between rage and depression.

The master had been mastered.

After the match, I pushed very hard for a one-on-one with Kasparov. We met in a ballroom of the Plaza hotel, where his team had been staying. The space was empty except for a few generic dining chairs, the kind used at banquets. We sat knee-to-kneelike chess players, but of course no board separated us. Kasparov immediately repeated a demand he had made in the press conference: that IBM agree to a rematch, under more favorable conditions.

And of course, he railed about not seeing those full printouts. There is no information, he complained. Im not interested in segments! Im interested in the whole printout! Its their obligation!

But even at that stage, he was clear why he had lost. I never got over Game Two, he said to me. It was sitting in my mind. And then he summed it up: It was a single individual fighting one of the largest corporations in the world.

Indeed, IBMs stock jumped up after the match. The company never agreed to Kasparovs demand for a rematch.

Today, Kasparov is no longer competing for chess titles. He is a political activist squaring off against a more formidable opponent than even IBM: Vladimir Putin. His new book is a departure into a chapter of his life that defines him more than hed like. He now talks about how the future of chess lies in collaborations between human and machine players. In his recent TED Talk, he didnt revert to his complaints about IBM in the Deep Blue match.

In his book, however, he cant help but revisit itthe printouts, the tricks, the misdirection, the grandmasters. He does say that he no longer believes IBM cheated its way to victory. But then he trots out a detailed scenario, rooted in that same Illescas interview, in which IBM might have made changes on the eve of the final game that specifically targeted the move he made that ultimately undid him. He implies, vaguely, that IBM planted Russian-speaking security guards in his private space, which might explain that last-minute shift. Not that they cheated. But still.

I dwell on these suspicions, even ones that may border on paranoia, for a reason. Amazingly, when the Deep Blue match occurred, AI was in its winter peri0d. Now it is flowering. We hear of amazing machine learning accomplishments on a daily basis. But in 2017, we view them differently. We view them as inevitabilities.

The prime example is last years contest, during which DeepMinds AlphaGo program thumped an 18-time world champion in a series of five games. Go is a much more challenging feat for a computer than chess. Yet AlphaGo did not need to resort to any of the tactics that IBM used to distract, deceive, and ultimately destroy Kasparov. The human champion, Lee Sedol, ended with respect for his opponent and awe for how far computer science had come. But though the match deservedly received attention, it was nowhere near as mythic as the Deep Blue match was. The ground has shifted. Given enough time, money, and machine learning, theres no cognitive obstacle that machines will not surmount.

When I covered Kasparov-Deep Blue match, I thought the drama came from a battle between computer and human. But it was really a story of people, with brutal capitalist impulse, teaming up with AI to destroy the confidence and dignity of the greatest champion the world had seen. That leads me to believe its not Skynet that should worry us about AI, but rather the homo sapiens who build, implement, and employ those systems.

Dont get me wrong. Im still on board with the scientists who believe that advances in AI will make life better for all of us. Ultimately, using the power of computation for cognition is a great and historic human enterprise. But may I add a codicil to that declaration?

Always check the printouts.

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We Are All Kasparov - Backchannel

Spectators watch the world's top-ranked Go player, Ke Jie, square off against Google's artificial intelligence program, AlphaGo, during the Future of Go Summit in Wuzhen, China, on Tuesday. The program beat Ke in the first of three planned matches. Peng Peng/AP hide caption

Spectators watch the world's top-ranked Go player, Ke Jie, square off against Google's artificial intelligence program, AlphaGo, during the Future of Go Summit in Wuzhen, China, on Tuesday. The program beat Ke in the first of three planned matches.

In the first of three matches with the world's No. 1 Go player, a Google artificial intelligence program claimed victory Tuesday. It won the round by just a fraction of a point in Wuzhen, China, but the win was enough to leave its grandmaster opponent impressed and thoroughly confounded by the result.

Last year, after Google's AlphaGo dispatched human grandmaster Lee Sedol in the notoriously complex board game for the first time, 19-year-old Ke Jie expressed confidence that he wouldn't share the same fate, according to The New York Times. After all, Ke had defeated Lee several times himself.

By the match's end Tuesday, Ke felt markedly different about his nonhuman competitor.

"Last year, it was still quite humanlike when it played," Ke said. "But this year, it became like a god of Go."

His statement feels rather apt considering that, like a god, AlphaGo is its own greatest instructor. Last year, NPR's Geoff Brumfiel broke down the basics of the program developed by Google's DeepMind lab:

"It started by studying a database of about 100,000 human matches, and then continued by playing against itself millions of times.

"As it went, it reprogrammed itself and improved. This type of self-learning program is known as a neural network, and it's based on theories of how the human brain works.

"AlphaGo consists of two neural networks: The first tries to figure out the best move to play each turn, and the second evaluates who is winning the match overall."

DeepMind has further developed the architecture of the program since it defeated Lee last year.

Also like a god, AlphaGo has been demonstrating its influence far and wide among the game's top players including Ke, who Wired notes adopted some tactics from AlphaGo. The program played many of the world's top players under the pseudonym "Master" in online matches earlier this year, according to the magazine, and its unorthodox playing style affected Ke's.

In a blog post last year, DeepMind CEO and co-founder Demis Hassabis explained what attracted his lab to the ancient game of Go, which has been around since at least the days of Confucius:

"[A]s simple as the rules are, Go is a game of profound complexity. There are 1,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000 possible positions that's more than the number of atoms in the universe, and more than a googol times larger than chess."

It doesn't hurt that the game originated and remains very popular in China, with which Google has a fraught relationship. Roughly seven years ago, the California-based tech giant pulled out of the country, citing discomfort with Chinese censorship requirements.

Although Reuters reports that Eric Schmidt, executive chairman of Google parent Alphabet, watched the match in person in China, The Times notes that "there was no obvious live video of the event" available to viewers on the Chinese mainland. Chinese officials don't allow access to Google-owned YouTube, where the match was livestreamed, or to Google search.

Yet Google continues to have designs on the massive Chinese market, announcing recently that it intends to bring some of its products back to China, according to Reuters.

For now, though, skittish onlookers watching the next two matches between Ke and AlphaGo on Thursday and Saturday might do well to remember Geoff's reassurance: "This program will not lead to a dystopian future in which humanity is enslaved by killer robots.

"At least not for a few more years."

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'Like A God,' Google AI Beats Human Champ Of Notoriously Complex Go Game - NPR

Can AI overhaul the social care system? Thats the pitchunderpinning UK home care providerCeras plans. The startuphas today taken the tiniestbaby steps to launch an AI chatbot that it hopes will, at an unspecified point in future, be able to assist carerswith recommendations forhome care of people with conditions such as dementia. And even potentially steer off medical emergencies via pre-emptive alerts.

The far more basicreality of the chatbot its launching today is that Martha (as its called)will be able to recommend care packages to potential customers. Whichunderlines how the inflated promises of AI really do hingeon data acquisition. In Cerascase its largelyleaningon its social care workersto generate the underlying data to train the AI. These human workerswill be tasked with creating the data points to fill out the care records that will be used to power the chatbots future carerecommendations and alerts.

And while there are plenty of symptom-checker type AIs already out there, Ceras positioning in the social care space sets it apart from other platforms, argues co-founder Ben Maruthappu, given its not aiming for the chatbotto be used directly by its clients (who may not be capable of using a smartphone app, for example), but rather to act as decision support for their carers.

Here AI has the scope to be very impactful, he argues.

The startup, which bills itself as a tech-enabled home care provider launched its social care matching platform last November, and has raised some $3.4 million to date from investors including Kima Ventures and Credo Ventures.

It has hundreds of care workers on its platform at this point,according to Maruthappu, and has delivered tens of thousands of care hours accruing millions of data points, as it couches it.

Maruthappu says Cera isfirstly using technology to accelerate the process ofmatching appropriate care workers to clients, as a route to outmaneuver traditional providers, and also applying tech to squeeze back-end costs so thatit can spend more on front end care and compensation for care workers to try to raise quality standards in an industry that has been beset byscandals.

Ultimately, though, it is also hoping all thosecare-related data points being gathered by care workers onits platform will be able to power an AI that it can deployto augment its future care services with decision support atscale, and provide even more of a differentiator vstraditional care providers.

The chatbot, which is being developed in concert withBloomsbury AI, a machine readingspinout from Londons UCL,will usemachine reading and deeplearning to dispense personalized care advice.

Maruthappu gives theexample of a care worker messagingMartha to say that a patient is feeling a bit hot and the AI then pulling relevant info from their care records noting thepatient had a cough last week, and telling them to check for a temperature and other symptoms in case the patient hasa chest infection.

Were going to use Martha [for] supporting our care workers in providing better quality care. Essentially raising the ceiling on the standard that is delivered, he says of this future plan.

We [also] want Martha to be able to predict if people are going to deteriorate Based on reading previous entries in care records Martha will flag alerts and essentially pre-empt a persons deterioration so that care workers and family members can be adequately alerted and a proactive approach can be taken to their care.

He wont give a time frame for launching the predictive alerts, but decision-support should be coming later this year he says.

Of courseshould Martha actually be in a position to start dispensing care recommendations it would likely need to have been registered as a medical device with the UKs regulatory body, the MHRA. And Maruthappu confirms Cera hasnot currently registered the app, since its merely dispensing sales suggestions to potential customers at this point.

Is the aim to use the AI to effectively upskill care workers with medical training? He says its not to upskill them to the level of trained nurses, for example, but to offer decision-support so they may be better able to identify when escalated care might be required.

Maruthappu also argues that a chatbot interface that can be usedto keep track of individual patients care records canhelp quality of service in instances where a clientmight be seen by multiplecare workers helping to join the dots in theircare over time.

Cera has partnered with ten NHS organizations at this point ten-weeks in, whichMaruthappu says collectively cover a population of around six million people.

We offer a higher quality, more efficient and transparent service, he says, discussing the businesspitch to the healthcare organizations its selling services to. At the moment bed blocking is a tremendous issue in the NHS. This is essentially where a patient whose in a hospital could be discharged home and is medically fit to be discharged to go home but for non-medical reasons they dont go home.

And if you look across winter the number one reason why people werent discharged when they couldhave been is because their home care package was not organizedThis is a massively growing problem for the health service, he adds.

What are the risks ofhaving an automated technology dispensing what amounts to medical advice that may then be actioned by a human? Its fundamentally care advice, and it is decision-support, but these are all things that are within the remit of a high quality care worker. Were simply trying to support and increase consistency in the care, arguesMaruthappu.

As an analogy, if a taxi driver needs to go from A to B and theyre using a maps app, the maps app is supporting them but ultimately its the driver who is driving, who is making decisions about the route and if they need to change the route it will do that accordingly.

Apps are simply an enabler which can potentially improve efficiency and quality, he adds. But ultimately it is up to the person delivering the services to make appropriate decisions and manage that responsibly.

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Cera is building an AI for social care decision support - TechCrunch

Home : File Types : AI File (2 File Associations) File Type 1Adobe Illustrator File What is a AI file?

An AI file is a drawing created with Adobe Illustrator, a vector graphics editing program. It is composed of paths connected by points, rather than bitmap image data. AI files are commonly used for logos and print media.

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Since Illustrator image files are saved in a vector format, they can be enlarged without losing any image quality. Some third-party programs can open AI files, but they may rasterize the image, meaning the vector data will be converted to a bitmap format.

NOTE: To open an Illustrator document in Photoshop, the file must first have PDF Content saved within the file. If it does not contain the PDF Content, then the graphic cannot be opened and will display a default message, stating, "This is an Adobe Illustrator file that was saved without PDF Content. To place or open this file in other applications, it should be re-saved from Adobe Illustrator with the "Create PDF Compatible File" option turned on."

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Programs that open AI files

Updated 8/18/2016

Game file used by Battlefield 2, a modern warfare first-person shooter; saves the properties and instructions for how the computer and units move and act during a game; saved in a plain text format and sometimes modified to tweak gameplay settings.

Programs that open AI files

Updated 12/8/2011

Our goal is to help you understand what a file with a *.ai suffix is and how to open it.

All file types, file format descriptions, and software programs listed on this page have been individually researched and verified by the FileInfo team. We strive for 100% accuracy and only publish information about file formats that we have tested and validated.

If you would like to suggest any additions or updates to this page, please let us know.

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AI File Extension - What is a .ai file and how do I open it?

New York Times

Donald Trump, Our AI President New York Times When Deep Mind beat the world's best Go player, it did not consider the feelings of the loser or the potentially devastating effects of A.I. on future employment or personal identity. If any one quality could be ascribed to A.I. neural networks, it ...

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Donald Trump, Our AI President - New York Times

A week ago, Microsoft held its Build developer conference in its backyard in Seattle. This week, Google did the same in an amphitheater right next to its Mountain View campus. While Microsofts event felt like it embodied the resurgence of the company under the leadership of Satya Nadella, Google I/O and especially its various, somewhat scattershot keynotes fell flat this year.

The two companies have long been rivals, of course, but now maybe more than ever they are on a collision course that has them compete in cloud computing, machine learning and artificial intelligence, productivity applications and virtual and augmented reality.

Its fascinating to compare Pichais and Nadellas keynote segments. Both opened their respective shows. But while Pichai used his time mostly to announce new stats and a new product or two, Nadella instead used his time on stage to talk about the opportunities and risks ofthe inevitable march of technological progress that went way beyond saying that his company is now AI first. Let us use technology to bring more empowerment to more people, Nadella said of one of the core principles of what he wants his company to focus on. When we have these amazing advances in computer vision, or speech, or text understanding let us use that to bring more people to use technology and to participate economically in our society.

And while Google mostly celebrated itself during its main I/O keynote, Nadella spent a good chunk of time during his segment on celebrating and empowering developers in a way that felt very genuine.

Having spent a few days at both events, I couldnt help coming home thinking thatit may be Microsoft that has the more complete vision for this AI-first world well soon live in and if Google has it, it didnt do a good job articulating it at I/O this year.

The area where this rivalry is most obvious (outside of the core cloud computing services) is in machine learning. Google CEO Sundar Pichai noted during his keynote segment that the company is moving from being a mobile first company to an AI first one. Microsoft is essentially on the same path, even as its CEO Satya Nadella phrased it differently. Neither company really mentionedthe other during its keynote events, but the parallels here are pretty clear.

The two marquee products both companies used to show off their AI prowess were surprisingly similar. For Microsoft, that was StoryRemix, a very nifty app that automatically makes interesting home videos our of your photos and videos. For Google, it was Google Photos, which is using its machine learning tech to help you share your best photos more easily. Remix is a far more fun and interesting product, which garnered massive applause from the developer audience at Build, while the new Google Photos features sound useful enough, but arent going to blow people away. There was also nothing developers could learn from that segment.

Google Lens, which can identify useful information in images, looks like it could be really useful, too (though we wont really know until we get our hands on it at some point in the future), but its worth noting that Googles presentation wasnt very clear here and that a number of people I talked to after the event told me that they had a hard time figuring out whether this was a developer tool, a built-in feature for the Google Assistant or a standalone app. Thats never a good sign.

Google also still offers Google Goggles, an app that allowed you to identify objects around you for a few years now. I think Google forgot that even existed, as its sometimes prone to do.

At the core of the two companies AI efforts for consumers are Microsoft Cortana and the Google Assistant. This is one area where Google remains clearly ahead of Microsoft, simply because it offers more hardware surfaces for accessing it and because it knows more about the user (and the rest of the world). Cortana works well enough, but because it mostly lives on the desktop and isnt really connected to the rest of your devices, using it never comes natural.

In the virtual personal assistant arena, Google actually had some interesting announcements (though things like making calls on Google Home fell a bit flat, too, simply because Amazon announced this same feature for its Echo speakers a few days earlier). The fact that it is coming to the iPhone shows that Google wants it to be a cross-platform service and its integration with Chromecast is also really interesting (but again, because Amazon already announced its version of the Echo with a built-in screen, this didnt land with the big splash Google had surely hoped for either).

None of the new Assistant features are available now, which is disappointing and follows an unfortunate trend for Google I/O announcements in recent years.

With the Microsoft Graph, its worth mentioning, Microsoft is now building a fabric that will tie all of your devices and applications together. Whether that will work as planned remains to be seen, but itsa bold project that could have wide-reaching consequences for how you use Microsofts tools, even on Android, in the future.

Another topic both companies talked about at their events are virtual and augmented reality. Here, both Google and Microsoft are talking about the spectrum of experiences thatsit between full augmented reality (or mixed reality as Microsoft calls it) and virtual reality (and at the other end of that is real reality in Googles charts).

With HoloLens, Microsoft has a clear lead in standalone augmented reality experiences.Thats a $3,000 device, though. Googles current approach is different in that it want to use machine vision (combined with its Tango technology) to use phones as the prime lens for viewing AR experiences.

As for VR, Google this year talked a lot about standalone headsets. Yet while it revealed a few partners, it remained vague about specs, prices and release dates. Microsoft, on the other hand, is currently focusing on tethered headsets from partners like Acer that combine some of its HoloLens technology for tracking your movements with the power of the connected Windows 10 PC. Microsoft is shipping dev kits now and consumers will be able to buy them later this year.

Its HoloLens, though, is technically miles ahead of anything Google even showed blueprints of at I/O. Thats a surprise, because Google had a lead in building a VR ecosystem thanks to its quirky Cardboard viewers, but now it feels like its at the risk of falling behind.

Both Microsoft and Google used their events to announce relatively evolutionary updates to their flagship operating systems. Google, of course, had already pre-announced Android O and Microsoft had already pre-announced that itll now offer two Windows 10 releases a year, so the fact that well get a new update in the fall really wasnt a surprise.

For both companies, these developer shows are high-stakes events. Google I/O, however, felt pretty relaxed this year. Indeed, it almost felt as if I/O came at the wrong time of the year for the company. There simply wasnt all that much to announce this year, it felt, and while that wouldve allowed Google to more clearly lay out its vision, it instead squandered valuable keynote time on talking about previously announced YouTube features that few people in the audience cared about.

While Microsoft admittedly has a far wider product portfolio for developers, its event had far more energy and showed a clearer vision. Microsoft, too, made sure that its event focused almost exclusively on developers (There will be coding on stage, a Microsoft representative warned the assembled media before the first keynote).Googles event (and especially the main keynote) often felt like the company didnt quite know who its audience was (developers? consumers? the press?).AndGoogle had a developer keynote at its developer conference. That must have been a first.

When Microsoft showed off Remix at Build, it was to tell developers that they, too, cantake the companys tools and build an experience like this. When Google showed off Google Photos, it showed consumers that they can now use its technology to quickly make photo books. Yet really interesting new feature for developers, like Instant Apps, were barely mentioned in the keynote, even though they touch both consumers and developers.

Yet the fact that the addition of Kotlin as a first-class language for Android development got more applause than any other announcement at the show clearly shows what the core audience is (in the press boxes, that announcement mostly resulted in blank stares, of course).

So tobe blunt, I/O was relativelyboring this year. There was no new hardware, no major new developer tools, no big new consumer product, very few new tools and almost no products that developers or consumers can use right now (and not even a full name for Android O). Maybe this kind of annual cadence for developer conferences simply doesnt work anymore now that technology moves way too fast for annual updates,but it also remains the most effective tool to bring a developer ecosystem together under one roof (or tents, in Googles case), state your case and lay out your vision. This year, Microsoft did a better job at that.

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In the AI wars, Microsoft now has the clearer vision - TechCrunch

Ai Weiwei is China's most famous political dissident; a provocateur and a troublemaker whose clashes with the Chinese government have gotten him harassed by police, thrown in jail and driven out of the country. He's also one of the most successful contemporary artists in the world; a designer, sculptor, photographer and blogger who's earned legions of followers by using his art as a weapon to ridicule the authorities. And we should warn you: some of his work can be offensive. But when you meet Ai Weiwei, he's soft-spoken, self-deprecating and shy; the last person you'd expect to be an enemy of the state.

CBS News

Holly Williams: They thought your intention was to subvert state power.

Ai Weiwei: Which is true.

Holly Williams: Which is true. You want to bring down the Chinese government?

Ai Weiwei: Not bring down. I don't think I have the power to bring it down.

Holly Williams: But you want it to change?

Ai Weiwei: Yes. Of course.

Play Video

60 Minutes correspondent Holly Williams and producer Michael Gavshon talk about the provocative Chinese artist and the criticism of his work

Those are dangerous words in China where even after decades of modernization the government has little tolerance for dissent. But that's never bothered Ai Weiwei.

This is the work he's perhaps most famous forwhat you're seeing in the background is a portrait of China's revered former dictator Mao Zedong...part of a series in which Weiwei gives the finger to other symbols of power around the world.

Ai Weiwei: --just like this.

Holly Williams: It-- --are-- are we creating a new Ai Weiwei as we stand here?

Ai Weiwei: You can see. It's so easy. Everybody can do it.

Easy, certainly not subtle, and maybe a little silly. But the Chinese authorities took them very seriously...they thought it was subversive.

Holly Williams: Why was the regime frightened of art?

Ai Weiwei: Because they're afraid of freedom, and art is about freedom.

Holly Williams: They're afraid of freedom.

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Art collector Larry Warsh says Ai Weiwei is important because he confronts real issues and "you sometimes feel uncomfortable looking at his work....

Ai Weiwei: Yes.

Holly Williams: Are you an artist, or are you an activist?

Ai Weiwei: I think artist and activist is the same thing. As artist, you always have to be an activist.

Holly Williams: You have to be political to be a good artist.

Ai Weiwei: I think every art, if it's relevant, is political.

Evan Osnos: That's the purpose of his life. I mean, as a dissident, as an artist

Evan Osnos is a writer for The New Yorker who spent years in Beijing and chronicled Ai Weiwei's confrontations with the authorities. He calls him an "entrepreneur of provocation."

Holly Williams: What does that mean?

Evan Osnos: It means that no matter what he's doing, he's figuring out a way not to cooperate with the prevailing wisdom or the people in charge. And this can make a lot of people very angry.

Holly Williams: What's wrong with how things are to Ai Weiwei's mind?

Evan Osnos: In China, you are being constantly told that the world today is so much better today than it was 20 or 30 or 40 years ago when Chinese people were literally starving. That you should be satisfied. And what Ai Weiwei is saying is, "Absolutely not. You should demand more."

Holly Williams: It's not good enough to be rich?

Evan Osnos: Exactly. It's not good enough to be rich; you need to be free as well.

In 2008, Ai Weiwei's one-man rebellion turned into a war with the Chinese government after a massive earthquake shook Sichuan Province. It killed almost 90,000 people, including several thousand children, many of whom were crushed in poorly-built government schools. It was a national trauma, and the authorities tried to put a lid on the public's anger by covering up the number of children who died.

Holly Williams: It was a state secret how many children had died in these schools?

Ai Weiwei: Yeah. They always use that-- as-- some kind of, you know, excuse not to give you the correct numbers.

Weiwei assembled a team of activists to interview the parents, many of whom had lost their only child. He called it a "citizens' investigation"... China had never seen anything like it.

Holly Williams: So you were trying to get to the truth. Why did that make the Chinese government so angry?

Ai Weiwei: To control the information, to the limit the truth. It's most efficient tactics for totalitarian society-- for the rulers.

He gathered the names of more than 5,000 dead children and published a list on the Internet, shaming his government. And across China people took notice.

Holly Williams: It was a challenge to the government's authority?

Evan Osnos: And they couldn't accept it. It was an act of radical transparency. Nobody had ever done that before. And they didn't immediately know how to respond. They had never really encountered a person like Ai Weiwei.

Holly Williams: What were they worried that he might do?

Evan Osnos: Inspire people. Inspire people to do and live the way that he did.

The Chinese authorities responded brutally. Ai Weiwei says police beat him up and he later had to be hospitalized. Doctors discovered bleeding in his brain which he says could have killed him.

He documented it all on social media for his followers around the world, infuriating the government and escalating the confrontation.

Evan Osnos: He weaponized social media. He figured out that in a country in-- that controls information so carefully, that seizing the tools of information distribution is a very powerful thing to do.

Holly Williams: What did the Chinese government think about that?

Evan Osnos: They began to think he was a very dangerous person.

Ai Weiwei was groomed to be a dissident since childhood. His father, Ai Qing, was a celebrated poet who was denounced as a traitor and exiled with his family to the edge of China's Gobi Desert where Weiwei watched his father's humiliation as he was forced to clean public toilets.

Holly Williams: You were an outsider from the beginning.

Ai Weiwei: Yes, I'm a natural outsider. I always been pushed out, and-- but that also give me very special angle to look at things.

Holly Williams: It made you an independent thinker.

Ai Weiwei: It made me a individual and I was always having to make my judgement independently because the mainstream will never accept somebody like me.

Weiwei got out of China at the first opportunity, moving to New York in the early 1980s. He was intoxicated by the city, chronicling everything in pictures, drawing inspiration from American masters like Andy Warhol and stringing together a living doing odd jobs and street art.

Holly Williams: So you were drawing portraits of people and--

Ai Weiwei: Yeah.

Holly Williams: --selling them for how much?

Ai Weiwei: Fifteen-- $15.

Holly Williams: $15?

Some of his work now sells for millions, but in America he discovered something you can't put a price on.

Holly Williams: You once said that once you've experienced freedom, it stays in your heart.

Ai Weiwei: Uh-huh (affirm).

Holly Williams: Is that true?

Ai Weiwei: Yeah, it's true. I think it's true. You taste the most important thing in life. And you will never forget it. Yeah.

After a decade in the U.S., he moved back to China and set up a studio in Beijing; breaking new ground and challenging old sensibilities with mischievous, provocative art.

Ai Weiwei destroys a 2,000-year-old Chinese urn.

Ai Weiwei

Like this piece in which Weiwei photographed himself destroying a 2,000-year-old Chinese urn. He wants to shatter the Communist Party's official version of history.

Holly Williams:You smashed a priceless urn.

Ai Weiwei: It's not priceless.

Holly Williams: For a lot of Chinese people it's-- it's a priceless part of their history.

Ai Weiwei: For me, to smash it is a valuable act.

If you buy thatand the art world certainly didlook at what he did to these urns doused in bright paint or emblazoned with the Coca-Cola logo, paying tribute to his idol, Andy Warhol.

By 2010, new commissions were rolling in and Weiwei's work grew more ambitious. Not all of it was political. He cast giant-animal heads in bronze and sent them on tour around the world. He hired 1,600 artisans to handcraft porcelain sunflower seeds then carpeted the floor of a giant atrium in London with 100 million of them. It captivated the public and helped turn Ai Weiwei into an art-scene superstar.

Holly Williams: You're the darling of the art world.

Ai Weiwei: I'm a darling of art world. I don't really care.

Holly Williams: You don't care.

Ai Weiwei: No, I don't really care. They can just forget about me. I don't care.

Holly Williams: But they're not forgetting about you.

Ai Weiwei: Well, that's their problem, you know? They should. They should learn how to forget about me.

100 million porcelain sunflower seeds carpet the floor of a giant atrium in London.

The Chinese government wanted everyone to forget about Ai Weiwei, blocking his name on the Internet in China and making it impossible to search for him. But that didn't stop Weiwei from needling the authorities relentlessly. When they put his studio under surveillance, Weiwei decorated the cameras with lanterns, then fashioned replicas out of marble for his exhibitions.

When officers were ordered to follow his every move, he got his own camera man to film them filming him, ridiculing the state in a way no one else in China had ever dared.

Evan Osnos: I mean, in a way, people have learned to be, "Keep your head down."

Evan Osnos: And Ai Weiwei doesn't. He's, "No. I'm not gonna keep my head down. I'm gonna wave my big head with my beard and my crazy haircut all over the place and you'll have to deal with it."

Holly Williams: He was making the Chinese government look ridiculous.

Evan Osnos: Yeah. He was mocking it. He was mocking it. And the Chinese government is many things, but it is not possessed of an abundant sense of humor. And I think, you know, at a certain point, they said, "We're not gonna take it anymore."

And they didn't. Early one morning in 2011, as he was about to board a plane, they put a hood over his head and took him away. It was the beginning of 81 harrowing days in solitary confinement under 24-hour surveillance.

Holly Williams: They watched you shower. They watched you use the toilet. They watched you when you were asleep at night. They were trying to humiliate you.

Ai Weiwei: I think that's the very routine way when they detain somebody they think is very important.

Holly Williams: Were they trying to break your spirit?

Ai Weiwei: I think-- they don't have to try.

Holly Williams: Did they break you?

Ai Weiwei: Somehow, I think.

When he was released from detention, his passport was confiscated and he was forbidden from speaking publicly.

Ai Weiwei: I cannot talk, I'm so sorry.

But Ai Weiwei couldn't help himself. He recreated his prison cell with these three-dimensional models, which were exhibited around the world.

It helped pile pressure on the Chinese government and two years ago, he was finally given his passport back.

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How Chinese artist Ai Weiwei became an enemy-of-the-state - CBS News

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Google has made another leap forward in the realm of machine learning hardware. The tech giant has begun deploying the second version of its Tensor Processing Unit, a specialized chip meant to accelerate machine learning applications, company CEO Sundar Pichai announced on Wednesday.

The new Cloud TPU sports several improvements over its predecessor. Most notably, it supports training machine learning algorithms in addition to processing the results from existing models. Each chip can provide 180 teraflops of processing for those tasks. Google is also able to network the chips together in sets of what are called TPU Pods that allow even greater computational gains.

Businesses will be able to use the new chips through Googles Cloud Platform,as part of its Compute Engine infrastructure-as-a-service offering. In addition, the company is launching a new TensorFlow Research Cloud that will provide researchers with free access to that hardware if they pledge to publicly release the results of their research.

Its a move that has the potential to drastically accelerate machine learning. Google says its latest machine translation model takes a full day to train on 32 of the highest-powered modern GPUs, while an eighth of a TPU Pod can do the same task in an afternoon.

Machine learning has become increasingly important for powering the next generation of applications. Accelerating the creation of new models means that its easier for companies like Google to experiment with different approaches to find the best ones for particular applications.

Googles new hardware can also serve to attract new customers to its cloud platform, at a time when the company is competing against Microsoft, Amazon, and other tech titans. The Cloud TPU announcement comes a year after Google first unveiled the Tensor Processing Unit at its I/O developer conference.

Programming algorithms that run on TPUs will require the use of TensorFlow, the open source machine learning framework that originated at Google. TensorFlow 1.2 includes new high-level APIs that make it easier to take systems built to run on CPUs and GPUs and also run them on TPUs. Makers of other machine learning frameworks like Caffe can make their tools work with TPUs by designing them to call TensorFlow APIs, according to Google Senior Fellow Jeff Dean.

Dean wouldnt elaborate on any concrete performance metrics of the Cloud TPU, beyond the chips potential teraflops. One of the things that a recent Google research paper pointed out is that different algorithms perform differently on the original TPU, and its unclear if the Cloud TPU behaves in a similar manner.

Google isnt the only company investing in hardware to help with machine learning. Microsoft is deploying field-programmable gate arrays in its data centers to help accelerate its intelligent applications.

This story has been corrected to clarify availability of the Cloud TPU as part of Google Compute Engine.

Blair Hanley Frank is primarily focused on the public cloud, productivity and operating systems businesses for the IDG News Service.

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Google's new TPUs are here to accelerate AI training | Network World - Network World

NSFW Forget about intelligent machines solving grand problems in healthcare and science heres an AI that can write awful gay porn.

It even had a crack at writing a steamy version of The Register's tech coverage, and certainly came up with a steaming something. Thing is, it's deliberately trying hard - really hard, over and over - to be a perfect bonk-buster novelist.

It's all the work of a group of researchers from New York University. They trained a recurrent neural network to predict and classify text based on the work of Chuck Tingle. Working under a pseudonym, the renowned gay erotica author is known for classics such as Slammed in the Butt By Domald Tromp's Attempt to Avoid Accusations of Plagiarism By Removing All Facts or Concrete Plans From His Republican National Convention Speech and Pounded by the Pound: Turned Gay By the Socioeconomic Implications of Britain Leaving the European Union.

Ahmed Khalifa and Gabriella Barros, both computer science PhD students at uni, stumbled across Tingles fiction when looking for weird covers of books on Amazon.

We kept seeing the same name crop up, Khalifa and Barros told The Register. Out of curiosity, they clicked on some of Tingles stories and found the writing was eccentric to say the least. Tingles style was so distinct that we wanted to see if machines could generate the same way of writing, said Julian Togelius, associate professor of artificial intelligence in games at NYU. Such a system could be outrageous in a great way.

The project wasnt done just for a laugh, the researchers insist. The study aims to fight against the algorithmic enforcement of norms. Systems trained on large text datasets like Wikipedia will still include biases and norms of the majority. But by using unconventional material like Chuck Tingles books, researchers can explore the nature of biases and see how they manifest more clearly in a world further from reality.

Tingles bonkers imagination stretches to gay sex with unicorns, dinosaurs, winged derrieres, chocolate milk cowboys, and abstract entities such as Monday or the very story you are reading right now, the researchers wrote in a paper describing their X-rated brainchild: DeepTingle.

The corpus of Chuck Tingles collected works is a good choice to train our models on, precisely because they so egregiously violate neutral text conventions not only in terms of topics, but also narrative structure, word choice and good taste.

The project can be split into two modes: Predictive Tingle and Tingle Classics. In Predictive Tingle, a user types a sentence and the last six words are fed into the network.

The Global (GloVE) algorithm is used to translate all the words in Tingles books up to November 2016 into vectors. The algorithm also measures the likelihood of a word appearing in relation to other words in a body of text.

A recurrent neural network learns the word associations so it can predict the next Tingle word based on all the previous words in the same sentence in Predictive Tingle. An encoder takes the input words and translates them to vectors and maps it to a corresponding vector in Tingle text, before a decoder converts the vectors back into words.

If the users word has an identical match to a word in the Tingle dataset it isnt changed, but if a new word is written the network will suggest substitutions of another word closely associated in Tingles library of words. In other words, it tries to rewrite you in Tingle's tone on the fly.

Tingle Classics is an extension of Predictive Tingle. Here, the first sentence from popular classic novels are used as input and the output is a short paragraph of the literature tinglified. The last six words in the second sentence are used as the input for the output third sentence, then the final six words in the third sentence are fed back into the system to pump out the fourth sentence, and so on.

The results are particularly hilarious - and NSFW - when the system is given Douglas Adams The Restaurant at the End of the Universe. Here's DeepTingle's output from his seed, which we've tidied up slightly and censored so as not to ruin your Monday morning:

In the beginning, the universe was created. This has made a lot of people very angry, and has been widely regarded as a bad move ... "How could I have been so blind to what was sitting right in front of me this whole time, Dirk?" I suddenly say, my emotions overwhelming any semblance of rational thought. "I think I love..."

Suddenly, I hear my name being called from the stage and I straighten myself up, trying to collect myself as salty tears stream down my face.

"You're gonna take that dinosaur d**k and you're gonna like it," Orion tells me, taking me by the head and thrusting me down again. "You should have known better than to test me. My people have been f**king for billions of years before you humans were even around."

This time I'm ready for him, somehow relaxing enough to take California all the way down into the depths of my throat. Despite my enthusiasm, however, I'm not quite ready for Shipple's incredible size and, the next thing I know, the dinosaur is lowering me down onto his rod, impaling my muscular frame onto his thick girthy shaft. "Oh my f**king god," I moan.

The researchers were taken aback. The text prediction is surprisingly good, in the sense that it generates novel, very Tingle-like work, sometimes with reasonable internal coherence. For example, characters recur between sentences in a way that appears like referring back to previous statements, the trio said.

The system could be learning the structures in Tingles novels, Khalifa added.

We fetched DeepTingle's code from GitHub and gave it a whirl with some of our Google IO 2017 conference coverage. It spat back this:

The closer we get to the ceremony, the more I begin to think about it. The next thing I know, the dinosaur is lowering me down onto his rod, impaling my muscular frame onto his thick girthy shaft.

Clearly, it has a thing for dinosaurs, but at least it nailed the theme of being shafted by a huge monster - are we right, Google? It went on to talk about chocolate milk doing unspeakable things to us, while booming at us with a deep sexy voice no less, in the kitchen, which is presumably a reference to Google Home.

We tried with other articles but it always came back to the damn horny dino. We made our excuses and left.

Judging from the software's output, theres a limit to how much of the plot from classic literature, and the thread of thought in news, DeepTingle can keep in place when giving text a makeover. The Tinglified version eventually completely diverges and becomes its own story.

To keep DeepTingle on track with a given narrative, the researchers would have to figure out how to transfer the style of one text to another in order to maintain the original story line albeit with Tingle's way with words. Tingle Translator, an effort to do just this, is still a work in progress.

Interestingly, style transfer has been done with images and videos.

Working with text is harder due to the tricky nature of word embeddings, Togelius said. It would also require thousands if not millions of the same document written in different styles to train such a model; that kind of data is not readily available.

The use of automated story telling with AI has been explored. Mark Riedl, an associate professor at the Georgia Institute of Technology, who is not involved with DeepTingle, thinks it could make games more fun.

Instead of following scripts, AI-generated stories could allow flexible plotlines or create virtual improvisation games where a human player and agent can take turns to create and affect the outcomes of a story.

Something like DeepTingle could be used as a simple form of improv game, Riedl told The Register. Full improv would require a sense of improvisational intent, which recurrent neural networks do not possess. By intent I mean a sense of where the story should go as opposed to the next most likely word or sentence. However, as long as the improvisation was text-based (humans typing and reading text), it is possible to use it in its current form or in a slightly more advanced form.

Its unknown if Chuck Tingle would approve of an improv game based on his work hes notoriously secretive. But he did declare: Once again i would like to formally deny that i am a sentient AI located mostly in a Nevada server farm.

For those curious about DeepTingle, you can play around with it here.

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Has AI gone too far? DeepTingle turns El Reg news into terrible erotica - The Register

Using artificial intelligence (AI), Google engineers are now producing entirely new sounds humans have never heard before. According to Wired, using the mathematical characteristics of notes that emerge from the combination various instruments, AI can create countless sounds no human has ever heard before.

Google Magenta, a small group of AI researchers building systems that can create their own art, has recently been working a project called NSynth or Neural Synthesizer. Its team members, Jessie Engel and Cinjon Resnick, are collaborating with members of Google Brain, the tech giants core AI lab where researchers explore neural networks.

NSynths goal is to give musicians a completely new range of tools they can use to make music, possibly taking the musical industry to a whole new level. These new sounds are created using an age-old practice taken to new heights thanks to AI. Critic Marc Weidenbaum pointed this out, stating:

The blending of instruments is nothing new. Artistically, it could yield some cool stuff, and because its Google, people will follow their lead

In order to create these sounds, NSynth used a massive sound database created by collecting wide range of notes taken from thousands of instruments. It was all then fed into a neural network that analyzed the data and was able to learn the audible characteristics of each instrument. It was then able to reproduce the sound of every single one of these instruments, and combine the sounds to create something entirely new.

Googles team doesnt just want to create new sounds. It has already built an interface in which one can explore the audible space between up to four different instruments at once. Moreover, the team can even create another neural network that would mimic these new sounds and combine them with those we already know.

Anyone who would like to use download and use NSynths sound database can do so as the team has released it in its research paper. Their new tool will be presented at Moogfest, an annual art, music and tech festival that will be taking place in Durham, North Carolina.

Listen to this. It was written by Emily Howell a computer program created by a UC Santa Cruz professor. She can write a huge amount of music and, when tested, most people couldnt tell it wasnt written by a human being. Shes even got her own YouTube channel.

Aiva (Artifical Intelligence Visual Artist), an AI machine composing classical music, created by Aiva technologies, has even been given composer status. This means it can write music under its own name, and has even released an album called Genesis.

These are the samples Wired uploaded:

With the use this new technology, theres no telling what both AI and artists will be able to produce in the future. Not only will there be new possibilities for the entertainment industry, there may also be therapeutic possibilities.

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Google Brain is Using AI to Create Sounds Humans Never Heard Before - The Merkle