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Keeping up with an industry as fast-moving as\u00a0AI<\/a>\u00a0is a tall order. So until an AI can do it for you, here\u2019s a handy roundup of recent stories in the world of machine learning, along with notable research and experiments we didn\u2019t cover on their own.<\/p>\n This week in AI, we saw OpenAI, Anthropic, Google, Inflection, Microsoft, Meta and Amazon voluntarily commit<\/a> to pursuing shared AI safety and transparency goals ahead of a planned Executive Order from the Biden administration.<\/p>\n As my colleague Devin Coldewey writes, there\u2019s no rule or enforcement being proposed, here \u2014 the practices agreed to are purely voluntary. But the pledges indicate, in broad strokes, the AI regulatory approaches and policies that each vendor might find amendable in the U.S. as well as abroad.<\/p>\n Among other commitments, the companies volunteered to conduct security tests of AI systems before release, share information on AI mitigation techniques and develop watermarking techniques that make AI-generated content easier to identify. They also said that they would invest in cybersecurity to protect private AI data and facilitate the reporting of vulnerabilities, as well as prioritize research on societal risks like systemic bias and privacy issues.<\/p>\n The commitments are important step, to be sure \u2014 even if they\u2019re not enforceable. But one wonders if there are ulterior motives on the part of the undersigners.<\/p>\n Reportedly, OpenAI drafted an internal policy memo that shows the company supports the idea of requiring government licenses from anyone who wants to develop AI systems. CEO Sam Altman first raised the idea at a U.S. Senate hearing in May, during which he backed the creation of an agency that could issue licenses for AI products \u2014 and revoke them should anyone violate set rules.<\/p>\n In a recent interview with press, Anna Makanju, OpenAI\u2019s VP of global affairs, insisted that OpenAI wasn\u2019t \u201cpushing\u201d for licenses and that the company only supports licensing regimes for AI models more powerful than OpenAI\u2019s current GPT-4. But government-issued licenses, should they be implemented in the way that OpenAI proposes, set the stage for a potential clash with startups and open source developers who may see them as an attempt to make it more difficult for others to break into the space.<\/p>\n Devin said it best, I think, when he described it to me as \u201cdropping nails on the road behind them in a race.\u201d At the very least, it illustrates the two-faced nature of AI companies who seek to placate regulators while shaping policy to their favor (in this case putting small challengers at a disadvantage) behind the scenes.<\/p>\n It\u2019s a worrisome state of affairs. But, if policymakers step up to the plate, there\u2019s hope yet for sufficient safeguards without undue interference from the private sector.<\/p>\n Here are other AI stories of note from the past few days:<\/p>\n Technically this was also a news item, but it bears mentioning here in the research section. Fable Studios, which previously made CG and 3D short films for VR and other media, showed off an AI model it calls Showrunner<\/a> that (it claims) can write, direct, act in and edit an entire TV show \u2014 in their demo, it was South Park.<\/p>\n I\u2019m of two minds on this. On one hand, I think pursuing this at all, let alone during a huge Hollywood strike that involves issues of compensation and AI, is in rather poor taste. Though CEO Edward Saatchi said he believes that the tool puts power in the hands of creators, the opposite is also arguable. At any rate it was not received particularly well by people in the industry.<\/p>\n On the other hand, if someone on the creative side (which Saatchi is) does not explore and demonstrate these capabilities, then they will be explored and demonstrated by others with less compunction about putting them to use. Even if the claims Fable makes are a bit expansive for what they actually showed (which has serious limitations) it is like the original DALL-E in that it prompted discussion and indeed worry even though it was no replacement for a real artist. AI is going to have a place in media production one way or the other \u2014 but for a whole sack of reasons it should be approached with caution.<\/p>\n On the policy side, a little while back we had the National Defense Authorization Act<\/a> going through with (as usual) some really ridiculous policy amendments that have nothing to do with defense. But among them was one addition that the government must host an event where researchers are companies can do their best to detect AI-generated content. This kind of thing is definitely approaching \u201cnational crisis\u201d levels so it\u2019s probably good this got slipped in there.<\/p>\n Over at Disney Research<\/a>, they\u2019re always trying to find a way to bridge the digital and the real \u2014 for park purposes, presumably. In this case they have developed a way to map virtual movements of a character or motion capture (say for a CG dog in a film) onto an actual robot, even if that robot is a different shape or size. It relies on two optimization systems each informing the other of what is ideal and what is possible, sort of like a little ego and super-ego. This should make it much easier to make robot dogs act like regular dogs, but of course it\u2019s generalizable to other stuff as well.<\/p>\n And here\u2019s hoping AI can help us steer the world away from sea-bottom mining for minerals, because that is definitely a bad idea. A multi-institutional<\/a> study put AI\u2019s ability to sift signal from noise to work predicting the location of valuable minerals around the globe. As they write in the abstract:<\/p>\n In this work, we embrace the complexity and inherent \u201cmessiness\u201d of our planet\u2019s intertwined geological, chemical, and biological systems by employing machine learning to characterize patterns embedded in the multidimensionality of mineral occurrence and associations.<\/p>\n The study actually predicted and verified locations of uranium, lithium, and other valuable minerals. And how about this for a closing line: the system \u201cwill enhance our understanding of mineralization and mineralizing environments on Earth, across our solar system, and through deep time.\u201d Awesome.<\/p>\n<\/p><\/div>\n\n
More machine learnings<\/h2>\n