The week in AI: Google goes all out at I\/O as regulations creep up - Science and Nerds<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/scienceandnerds.com\/2023\/05\/15\/the-week-in-ai-google-goes-all-out-at-i-o-as-regulations-creep-up\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"The week in AI: Google goes all out at I\/O as regulations creep up - Science and Nerds\" \/>\n<meta property=\"og:description\" content=\"Source:https:\/\/techcrunch.com\/2023\/05\/13\/the-week-in-ai-google-goes-all-out-at-i-o-as-regulations-creep-up\/ The week in AI: Google goes all out at I\/O as regulations creep up 2023-05-15 22:12:13 Keeping up with an industry as fast-moving as\u00a0AI\u00a0is a tall order. So until an AI can do it for you, here\u2019s a handy roundup of the last week\u2019s stories in the world of machine learning, along with notable […]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/scienceandnerds.com\/2023\/05\/15\/the-week-in-ai-google-goes-all-out-at-i-o-as-regulations-creep-up\/\" \/>\n<meta property=\"og:site_name\" content=\"Science and Nerds\" \/>\n<meta property=\"article:published_time\" content=\"2023-05-15T22:12:13+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2023-05-15T22:12:15+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/scienceandnerds.com\/wp-content\/uploads\/2023\/05\/the-week-in-ai-google-goes-all-out-at-i-o-as-regulations-creep-up_6462ae3ead317.jpeg\" \/>\n\t<meta property=\"og:image:width\" content=\"711\" \/>\n\t<meta property=\"og:image:height\" content=\"399\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"admin\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"admin\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"9 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/scienceandnerds.com\/2023\/05\/15\/the-week-in-ai-google-goes-all-out-at-i-o-as-regulations-creep-up\/\",\"url\":\"https:\/\/scienceandnerds.com\/2023\/05\/15\/the-week-in-ai-google-goes-all-out-at-i-o-as-regulations-creep-up\/\",\"name\":\"The week in AI: Google goes all out at I\/O as regulations creep up - 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Keeping up with an industry as fast-moving as\u00a0 AI<\/a>\u00a0is a tall order. So until an AI can do it for you, here\u2019s a handy roundup of the last week\u2019s stories in the world of machine learning, along with notable research and experiments we didn\u2019t cover on their own.<\/p>\n

This week, Google dominated the AI news cycle with a range of new products that launched at its annual I\/O developer conference. They run the gamut from a code-generating AI meant to compete with GitHub\u2019s Copilot<\/a> to an AI music generator that turns text prompts into short songs<\/a>.<\/p>\n

A fair number of these tools look to be legitimate labor savers \u2014 more than marketing fluff, that\u2019s to say. I\u2019m particularly intrigued by Project Tailwind<\/a>, a note-taking app that leverages AI to organize, summarize and analyze files from a personal Google Docs folder. But they also expose the limitations and shortcomings of even the best AI technologies today.<\/p>\n

Take PaLM 2<\/a>, for example, Google\u2019s newest large language model (LLM). PaLM 2 will power Google\u2019s updated Bard chat tool, the company\u2019s competitor to OpenAI\u2019s ChatGPT, and function as the foundation model for most of Google\u2019s new AI features. But while PaLM 2 can write code, emails and more, like comparable LLMs, it also responds to questions in toxic and biased ways.<\/p>\n

Google\u2019s music generator, too, is fairly limited in what it can accomplish. As I wrote in my hands on<\/a>, most of the songs I\u2019ve created with MusicLM sound passable at best \u2014 and at worst like a four-year-old let loose on a DAW<\/a>.<\/p>\n

There\u2019s been much written about how AI will replace jobs \u2014 potentially the equivalent of 300 million full-time jobs, according to a report<\/a> by Goldman Sachs. In a survey<\/a> by Harris, 40% of workers familiar with OpenAI\u2019s AI-powered chatbot tool, ChatGPT, are concerned that it\u2019ll replace their jobs entirely.<\/p>\n

Google\u2019s AI isn\u2019t the end-all be-all. Indeed, the company\u2019s arguably behind<\/a> in the AI race. But it\u2019s an undeniable fact that Google employs some of the top AI researchers in the world<\/a>. And if this is the best they can manage, it\u2019s a testament to the fact that AI is far from a solved problem.<\/p>\n

Here are the other AI headlines of note from the past few days:<\/p>\n

Meta brings generative AI to ads:<\/strong><\/a> Meta this week announced an AI sandbox, of sorts, for advertisers to help them create alternative copies, background generation through text prompts and image cropping for Facebook or Instagram ads. The company said that the features are available to select advertisers at the moment and will expand access to more advertisers in July.<\/li>\n
Added context:<\/strong><\/a> Anthropic has expanded the context window for Claude \u2014 its flagship text-generating AI model, still in preview \u2014 from 9,000 tokens to 100,000 tokens. Context window refers to the text the model considers before generating additional text, while tokens represent raw text (e.g. the word \u201cfantastic\u201d would be split into the tokens \u201cfan,\u201d \u201ctas\u201d and \u201ctic\u201d). Historically and even today, poor memory has been an impediment to the usefulness of text-generating AI. But larger context windows could change that.<\/li>\n
Anthropic touts \u201cconstitutional AI\u201d:<\/strong><\/a> Larger context windows aren\u2019t the Anthropic models\u2019 only differentiator. The company this week detailed \u201cconstitutional AI,\u201d its in-house AI training technique that aims to imbue AI systems with \u201cvalues\u201d defined by a \u201cconstitution.\u201d In contrast to other approaches, Anthropic argues that constitutional AI makes the behavior of systems both easier to understand and simpler to adjust as needed.<\/li>\n
An LLM built for research:<\/strong><\/a> The nonprofit Allen Institute for AI Research (AI2) announced that it plans to train a research-focused LLM called Open Language Model, adding to the large and growing open source library. AI2 sees Open Language Model, or OLMo for short, as a platform and not just a model \u2014 one that\u2019ll allow the research community to take each component AI2 creates and either use it themselves or seek to improve it.<\/li>\n
New fund for AI:<\/strong><\/a> In other AI2 news, AI2 Incubator, the nonprofit\u2019s AI startup fund, is revving up again at three times its previous size \u2014 $30 million versus $10 million. Twenty-one companies have passed through the incubator since 2017, attracting some $160 million in further investment and at least one major acquisition: XNOR, an AI acceleration and efficiency outfit that was subsequently\u00a0snapped up by Apple\u00a0for around $200 million<\/a>.<\/li>\n
EU intros rules for generative AI:<\/strong><\/a> In a series of votes in the European Parliament, MEPs this week backed a raft of amendments to the bloc\u2019s draft AI legislation \u2014 including settling on requirements for the so-called foundational models that underpin generative AI technologies like OpenAI\u2019s ChatGPT<\/a>. The amendments put the onus on providers of foundational models to apply safety checks, data governance measures and risk mitigations prior to putting their models on the market.<\/li>\n
A universal translator:<\/strong><\/a> Google is testing a powerful new translation service that redubs video in a new language while also synchronizing the speaker\u2019s lips with words they never spoke. It could be very useful for a lot of reasons, but the company was upfront about the possibility of abuse and the steps taken to prevent it.<\/li>\n
Automated explanations:<\/strong><\/a> It\u2019s often said that LLMs along the lines of OpenAI\u2019s ChatGPT<\/a> are a black box, and certainly, there\u2019s some truth to that. In an effort to peel back their layers, OpenAI is developing<\/a> a tool to automatically identify which parts of an LLM are responsible for which of its behaviors. The engineers behind it stress that it\u2019s in the early stages, but the code to run it is available in open source on GitHub as of this week.<\/li>\n
IBM launches new AI services:<\/a>\u00a0<\/strong>At its annual Think conference, IBM announced IBM Watsonx, a new platform that delivers tools to build AI models and provide access to pretrained models for generating computer code, text and more. The company\u00a0says the launch was motivated by the challenges many businesses still experience in deploying AI within the workplace.<\/li>\n<\/ul>\n
Other machine learnings<\/h2>\n
$\"\"$ <\/p>\n
Image Credits:<\/strong> Landing AI<\/p>\n<\/div>\n
Andrew Ng\u2019s new company Landing AI<\/a> is taking a more intuitive approach to creating computer vision training. Making a model understand what you want to identify in images is pretty painstaking, but their \u201cvisual prompting\u201d technique<\/a> lets you just make a few brush strokes and it figures out your intent from there. Anyone who has to build segmentation models is saying \u201cmy god, finally!\u201d Probably a lot of grad students who currently spend hours masking organelles and household objects.<\/p>\n
Microsoft has applied diffusion models in a unique and interesting way<\/a>, essentially using them to generate an action vector instead of an image, having trained it on lots of observed human actions. It\u2019s still very early and diffusion isn\u2019t the obvious solution for this, but as they\u2019re stable and versatile, it\u2019s interesting to see how they can be applied beyond purely visual tasks. Their paper is being presented at ICLR later this year.<\/p>\n
$\"\"$ <\/p>\n
Image Credits:<\/strong> Meta<\/p>\n<\/div>\n
Meta is also pushing the edges of AI with ImageBind<\/a>, which it claims is the first model that can process and integrate data from six different modalities: images and video, audio, 3D depth data, thermal info, and motion or positional data. This means that in its little machine learning embedding space, an image might be associated with a sound, a 3D shape, and various text descriptions, any one of which could be asked about or used to make a decision. It\u2019s a step toward \u201cgeneral\u201d AI in that it absorbs and associates data more like the brain \u2014 but it\u2019s still basic and experimental, so don\u2019t get too excited just yet.<\/p>\n
$\"\"$ <\/p>\n
If these proteins touch\u2026 what happens? Image Credits:<\/strong> EPFL<\/p>\n<\/div>\n
Everyone got excited about AlphaFold, and for good reason, but really structure is just one small part of the very complex science of proteomics. It\u2019s how those proteins interact that is both important and difficult to predict \u2014 but this new PeSTo model from EPFL<\/a> attempts to do just that. \u201cIt focuses on significant atoms and interactions within the protein structure,\u201d said lead developer Lucien Krapp. \u201cIt means that this method effectively captures the complex interactions within protein structures to enable an accurate prediction of protein binding interfaces.\u201d Even if it isn\u2019t exact or 100% reliable, not having to start from scratch is super useful for researchers.<\/p>\n
The feds are going big on AI. The president even dropped in on a meeting with a bunch of top AI CEOs<\/a> to say how important getting this right is. Maybe a bunch of corporations aren\u2019t necessarily the right ones to ask, but they\u2019ll at least have some ideas worth considering. But they already have lobbyists, right?<\/p>\n
I\u2019m more excited about the new AI research centers popping up with federal funding<\/a>. Basic research is hugely needed to counterbalance the product-focused work being done by the likes of OpenAI and Google \u2014 so when you have AI centers with mandates to investigate things like social science (at CMU)<\/a>, or climate change and agriculture (at U of Minnesota<\/a>), it feels like green fields (both figuratively and literally). Though I also want to give a little shout out to this Meta research on forestry measurement<\/a>.<\/p>\n
$\"\"$ <\/p>\n
Doing AI together on a big screen \u2014 it\u2019s science! Image Credits:<\/strong> Rich Ryan\/University of Minnesota<\/p>\n<\/div>\n
Lots of interesting conversations out there about AI. I thought this interview with UCLA (my alma mater, go Bruins) academics Jacob Foster and Danny Snelson<\/a> was an interesting one. Here\u2019s a great thought on LLMs to pretend you came up with this weekend when people are talking about AI:<\/p>\n
\n
These systems reveal just how formally consistent most writing is. The more generic the formats that these predictive models simulate, the more successful they are. These developments push us to recognize the normative functions of our forms and potentially transform them. After the introduction of photography, which is very good at capturing a representational space, the painterly milieu developed Impressionism, a style that rejected accurate representation altogether to linger with the materiality of paint itself.<\/p>\n<\/blockquote>\n
Definitely using that!<\/p>\n<\/p><\/div>\n
<\/br><\/br><\/br><\/p>\n
Science, Tech, Technology<\/br>
\n<\/br>
\nSource:https:\/\/techcrunch.com\/2023\/05\/13\/the-week-in-ai-google-goes-all-out-at-i-o-as-regulations-creep-up\/<\/a><\/br><\/br><\/p>\n","protected":false},"excerpt":{"rendered":"
Source:https:\/\/techcrunch.com\/2023\/05\/13\/the-week-in-ai-google-goes-all-out-at-i-o-as-regulations-creep-up\/ The week in AI: Google goes all out at I\/O as regulations creep up 2023-05-15 22:12:13 Keeping up with an industry as fast-moving as\u00a0AI\u00a0is a tall order. So until an AI can do it for you, here\u2019s a handy roundup of the last week\u2019s stories in the world of machine learning, along with notable […]<\/p>\n","protected":false},"author":1,"featured_media":32203,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"nf_dc_page":"","om_disable_all_campaigns":false,"pagelayer_contact_templates":[],"_pagelayer_content":"","_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[26,17,8],"tags":[],"class_list":["post-32202","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-science","category-tech","category-technology"],"yoast_head":"\nThe week in AI: Google goes all out at I\/O as regulations creep up - Science and Nerds<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/scienceandnerds.com\/2023\/05\/15\/the-week-in-ai-google-goes-all-out-at-i-o-as-regulations-creep-up\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"The week in AI: Google goes all out at I\/O as regulations creep up - Science and Nerds\" \/>\n<meta property=\"og:description\" content=\"Source:https:\/\/techcrunch.com\/2023\/05\/13\/the-week-in-ai-google-goes-all-out-at-i-o-as-regulations-creep-up\/ The week in AI: Google goes all out at I\/O as regulations creep up 2023-05-15 22:12:13 Keeping up with an industry as fast-moving as\u00a0AI\u00a0is a tall order. 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Other machine learnings<\/h2>\n<\/p>\nImage Credits:<\/strong> Landing AI<\/p>\n<\/div>\n