{"id":4978,"date":"2025-04-23T13:34:09","date_gmt":"2025-04-23T13:34:09","guid":{"rendered":"https:\/\/bullseye.ac\/blog\/?p=4978"},"modified":"2025-04-23T13:34:11","modified_gmt":"2025-04-23T13:34:11","slug":"god-like-ai","status":"publish","type":"post","link":"https:\/\/bullseye.ac\/blog\/learning\/god-like-ai\/","title":{"rendered":"God like AI"},"content":{"rendered":"\n<p>Ramesh Raskar was born in Nashik, India and he finished his engineering education in Electronics and Telecommunication from College of Engineering, Pune in 1991. He was an avid photographer in his college days and this interest led him to do a PhD in projector based 3d graphics from UNC, Chapel Hill. Raskar then joined Mitsubishi Electric Research Laboratories where he worked in computer vision. After 6 years at Mitsubishi labs, Ramesh joined academia.&nbsp; He became one of the youngest faculty members to get tenure at MIT Media Lab. Because of his work on camera software, a lot of professional photographers are being replaced by amateurs, without anyone noticing.<\/p>\n\n\n\n<p>At MIT, Ramesh developed a computational display technology that allows patients cataracts to perceive a focused image on a screen without wearing refraction-corrective spectacles. The technology uses customized filtering algorithms that pre-distort&nbsp; presented content. His lab produced a number of extreme high speed pictures using a femto-camera that took images at around one-trillion frames per second. They have also developed a camera to see around corners using bursts of laser light. Watch Ramesh\u2019s TED talk on ultra high speed photography here: <a href=\"https:\/\/www.ted.com\/talks\/ramesh_raskar_imaging_at_a_trillion_frames_per_second\">https:\/\/www.ted.com\/talks\/ramesh_raskar_imaging_at_a_trillion_frames_per_second<\/a><\/p>\n\n\n\n<p>Ramesh was in India in connection with the Kumbh. Being from Nasik, he has a connect with the festival &#8211; and he has been a regular observer \/ advisor since 2015. With digitalisation, the Nasik Kumbh went flawlessly with no stampedes and no masala for future Hindi film makers about brothers lost in the Kumbh mela. He believes that gatherings like the Kumbh are a major sandbox for all kinds of entrepreneurship. The 2025 Kumbh in Prayagraj is expected to host 40 cr visitors and create 10 b dollars in revenues. Ramesh, a true blooded generalist, has seeded an NGO to encourage Kumbh entrepreneurs, <a href=\"https:\/\/kumbhathon.com\/\">https:\/\/kumbhathon.com\/<\/a> His team has pledged to make the 2025 Kumbh as AI first.<\/p>\n\n\n\n<p>Here is an article from Forbes by John Werner, one of his students, which summarised most of his talk at COEP. I have added some of my own masala to the original essay.<\/p>\n\n\n\n<p>When we talk about \u201cgod-like AI\u201d what we really mean probably has to do with the convergence of trends that will supercharge these models and agents beyond what we can keep up with. In other words, AI may become so capable that as its contemporaries, we may end up being a little like cavepeople in the early world, less able to control and outthink other sentient forces in our environment.<\/p>\n\n\n\n<p>If all of this sounds esoteric, we can get a bit more of a real-world flavor from Ramesh Raskar who runs classes here at MIT on the future of AI (he\u2019s also head of the MIT Media Lab&#8217;s Camera Culture research group.) He presents a sort of AI mythology, if you will, that you can think of as maybe similar to the ancient Greek or Roman or Norse formulations, in its treatment of forces beyond our full understanding.<\/p>\n\n\n\n<p>Raskar talks about being \u201cthe voice of God\u201d in a hotline setup at Burning Man in Nevada, back in the landline days. Strangers would talk to him about their fears and secrets. This is exactly what AI is doing in our world, quoting Raskar: \u201cWhat we really need is a trusted, honest, impartial broker \u2013 the definition of God \u2013 we need a newfangled AI, a god-like AI, to do that orchestration.\u201d<\/p>\n\n\n\n<p>I found his examples interesting. You have Google Maps as the \u201cGod of traffic\u201d and ChatGPT as the \u201cGod of Public Information,\u201d but also, Raskar suggests, we might want even more connected \u201cgods\u201d involved. \u201cWhat we need,\u201d he says, \u201cis that deep-down information that\u2019s hidden well below the surface.\u201d&nbsp; What else could we have? Maybe Dall-E, the \u201cGod of art\u201d and Amazon the \u201cGod of instant delivery\u201d. Or, as Raskar notes, entities that can use a decentralized Internet to, say, sell products or find cures for diseases.<\/p>\n\n\n\n<p>I thought about his analysis of two big trends that are unlocking potential for god-like AI: one is ubiquitous compute, which I think many would agree we have in the age after Moore\u2019s Law, and the other is the proliferation of personal agents, AI entities that will do our bidding, or at least do things on our behalf. To quote Raskar: \u201cWhen you take these two trends and intersect them, suddenly AI can start thinking like a scientist.\u201d \u201cWe can wait for them to become smarter and smarter, like what we\u2019re doing now, or we can take these simple agents and let them start talking to each other.\u201d<\/p>\n\n\n\n<p>In Raskar\u2019s scheme of things, different AI agents will talk to each other. These would be decentralised &#8211; which means that no single entity will be in control, and so to some extent the fear of a <em>Matrix <\/em>film inspired power can be mitigated. Using a bad analogy, we can compare this to a drone swarm that is used to overwhelm defences. This is also good for data privacy and trying to set a stage where damage by bad actors is minimized. These specialised GPTs can be on the cloud to start with &#8211; but they may become smaller &#8211; allowing migrations to PCs. The components of this GOD can be compensated by a block chain model where service providers whose data is used to build the answers to disciple queries, can be compensated depending on the contribution made by the respective God to the query\u2019s solution.<\/p>\n\n\n\n<p>Raj Simhan, Ramesh\u2019s colleague at MIT, demo\u00e9d a God prototype &#8211; the God of research grant proposals. He took an idea from the audience &#8211; non-invasive thyroid problem detection in young women. This was fed into the agent &#8211; and at the end of 10 minutes, it had done a detailed primary research, come up with 3 alternate hypotheses that it would explore and a possible solution that would involve wearable tech, algos for preserving data privacy. It also assured us that no one else is doing something in this area. The last one turned out to be untrue, as the person who had asked the question had her daughter already working on this &#8211; with a grant made by DST.&nbsp;<\/p>\n\n\n\n<p>Here\u2019s the acronym that Raskar gives to explain the workings of the \u201cdeux ex machina\u201d \u2013 Global Orchestration of Decentralized AI. In terms of privacy, as he notes, we\u2019ll have to embrace a certain flavor of pseudo-anonymous delivery in order to facilitate these techniques.<\/p>\n\n\n\n<p>Another idea I thought was relevant is the study of incentives on data markets: how do you get people to participate? Raskar breaks down a system called \u201cCrowdX\u201d which relies on orchestration, discovery, visualization and decision support.<\/p>\n\n\n\n<p>In the end, we had a Q and A. I managed to squeeze in a question. In one of RR\u2019s talks he tells about how tech changed style. When sandpits started getting replaced by foam beds for high jumps, innovations like the Fosbury flop happened. I asked him about whether AI was providing a Fosbury Flop moment for education &#8211; how it feels to teach a class which doesn\u2019t need to be taught anymore.&nbsp;<\/p>\n\n\n\n<p>MIT, and most top US schools, allow AI to be used by students. RR used an analogy of today\u2019s AI being equivalent to yesterday\u2019s calculator. I pushed him further to share his take on non AI skills. He is on the verge of publishing a book on that soon &#8211; but let me get you a sneak preview: critical thinking, problem solving and understanding relations &#8211; are races that humans may still win against the AI bots!<\/p>\n\n\n\n<p><strong>Appendix &#8211; Raskar Gyan<\/strong><\/p>\n\n\n\n<p><em>Gyan on Inventions<\/em><\/p>\n\n\n\n<p>Ramesh is a modern day Edison &#8211; and seems to be working with his team to push in a fair number of innovations. Here is the Master sharing his bullet points on invention:<\/p>\n\n\n\n<ul>\n<li>Cleverness alone is not enough to become a good inventor<\/li>\n\n\n\n<li>Difference between problem-solving and invention \u2013 working in isolation can just solve a problem, while to invent you need give and take.<\/li>\n\n\n\n<li>Invention is all about people. If you don&#8217;t work with the right people you don&#8217;t get inspired to work in the right way.<\/li>\n\n\n\n<li>The true power of an inventor is less about expertise on one subject, but rather the ability to ask questions no one else is asking and follow the trail of answers as they are revealed.<\/li>\n\n\n\n<li>Inventor&#8217;s job is to think in an anti-disciplinary manner \u2013 look beyond disciplines<\/li>\n\n\n\n<li>To make a grand difference, ensure the problem you&#8217;re trying to solve is the right problem.&nbsp;<\/li>\n\n\n\n<li>The &#8220;spot probe&#8221; methodology is something every inventor needs to master. It is a continual cycle: Ask a lot of questions. Spot a lot of problems. Articulate those problems. Then probe their potential solutions.<\/li>\n<\/ul>\n\n\n\n<p><em>Gyan on PPTs<\/em><\/p>\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/lh7-rt.googleusercontent.com\/docsz\/AD_4nXfcWBP922NDmesK62O93IOUoTwdv0VhzrB447mDKcHfEvS5n4DDOt_lfs5tSEygzNaDFXJX6hDw3b5ZVOeFSnATio9WIxvYEPz7YpeDKl_s39u464TG_DUX_cjnkHn3Hvl01dp_oA?key=w5F522zGtHZQSrAWd2JO-A\" alt=\"\"\/><\/figure>\n\n\n\n<p>Creating intentional errors in your data can help do a plagiarism check with AI. Worth trying out for academicians.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Ramesh Raskar was born in Nashik, India and he finished his engineering education in Electronics and Telecommunication from College of Engineering, Pune in 1991. He was an avid photographer in his college days and this interest led him to do a PhD in projector based 3d graphics from UNC, Chapel Hill. Raskar then joined Mitsubishi &#8230; <a title=\"God like AI\" class=\"read-more\" href=\"https:\/\/bullseye.ac\/blog\/learning\/god-like-ai\/\" aria-label=\"More on God like AI\">Read more<\/a><\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_eb_attr":"","_uag_custom_page_level_css":"","footnotes":""},"categories":[51],"tags":[],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>God like AI - BullsEye<\/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:\/\/bullseye.ac\/blog\/learning\/god-like-ai\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"God like AI - BullsEye\" \/>\n<meta property=\"og:description\" content=\"Ramesh Raskar was born in Nashik, India and he finished his engineering education in Electronics and Telecommunication from College of Engineering, Pune in 1991. 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He was an avid photographer in his college days and this interest led him to do a PhD in projector based 3d graphics from UNC, Chapel Hill. Raskar then joined Mitsubishi&hellip;","_links":{"self":[{"href":"https:\/\/bullseye.ac\/blog\/wp-json\/wp\/v2\/posts\/4978"}],"collection":[{"href":"https:\/\/bullseye.ac\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/bullseye.ac\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/bullseye.ac\/blog\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/bullseye.ac\/blog\/wp-json\/wp\/v2\/comments?post=4978"}],"version-history":[{"count":1,"href":"https:\/\/bullseye.ac\/blog\/wp-json\/wp\/v2\/posts\/4978\/revisions"}],"predecessor-version":[{"id":4979,"href":"https:\/\/bullseye.ac\/blog\/wp-json\/wp\/v2\/posts\/4978\/revisions\/4979"}],"wp:attachment":[{"href":"https:\/\/bullseye.ac\/blog\/wp-json\/wp\/v2\/media?parent=4978"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/bullseye.ac\/blog\/wp-json\/wp\/v2\/categories?post=4978"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/bullseye.ac\/blog\/wp-json\/wp\/v2\/tags?post=4978"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}