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4K followers
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Aameek Singh liked thisAameek Singh liked thisIncredibly excited to announce that my first research paper, entitled "Supporting Sustainable Urban Design using Contrastive Learning and Large Language Models" has been officially published with IEEE after its presentation at the 2026 5th MEC International Conference on Advanced Data Analytics and Artificial Intelligence for Sustainable Smart Cities (ICADAAI 2026)! The paper is now officially available at IEEE Xplore! I am excited to focus what the future holds — for me it looks like LLM research! https://lnkd.in/eNyD7m9V (paper)
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Aameek Singh liked thisAameek Singh liked thisHonored to be named to the TIME100 AI 2026 list in the “Thinkers” category. As AI advances, I believe the questions ahead are increasingly about understanding—not only how far we can scale intelligence, but how deeply we can understand it, and how responsibly we can shape its progress. At 上海人工智能实验室, we will keep working with the global research community to explore these questions and advance AI for the benefit of all. Thank you to TIME for this recognition, and to all the colleagues and collaborators who make this work possible. Read more: https://lnkd.in/gpnRTnmy #TIME100AI #AIforScience #AISafety #ScientificDiscovery
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Aameek Singh liked thisTo understand whether we're making genuine progress on reasoning, we entered our AI models in five international STEM Olympiad competitions this year. The results: 🏅 Asian Physics Olympiad (APhO): Perfect score on the theory exam — gold medal 🏅 International Physics Olympiad (IPhO): Perfect score on the theory exam — gold medal 🥇 International Mathematical Olympiad (IMO): Gold medal, top 4% of human participants 🥇 International Chemistry Olympiad (IChO): Gold-medal level performance 🥇 Romanian Masters of Mathematics (RMM): Gold-medal level performance Three of these (APhO, IPhO, IMO) were live competitions and our solutions were submitted under real competition conditions and graded by the official judges using the same marking criteria applied to student contestants. A few things about the approach: • Models were internally trained versions from the Muse Spark family • Zero tool use: no search, no code interpreter, no calculator • Multi-agent orchestration with parallel reasoning We are excited about where this reasoning capability goes next; frontier research level across scientific domains and personal superintelligence. Super grateful to the organizing committees of APhO, IPhO, and IMO for supporting our live participation. We have deep respect for the contestants and organizers behind these competitions. 🙏 And proud of the MSL team that pulled this together!
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Aameek Singh liked thisAameek Singh liked thisI'm really excited to announce that two weeks ago, I joined Mirage. I’ve spent a lot of my career in startup-like moments inside large companies: Bloomberg in the early days of AI/ML, Reels when short-form video was just taking off, and Threads during a pretty wild growth curve. It felt like the right time to take the plunge into the startup world. More than ever, I believe small, motivated teams with real agency can do outsized work. Video is the space I keep coming back to. It is the format people consume most, but it is still incredibly hard to create well. AI makes it easy to demo something flashy. The much harder problem is helping people edit and create videos with real taste, control, and craft. Benchmarks don’t solve the parts users actually care about. Talking with Gaurav, Dwight, Justin, and the entire Mirage team made the opportunity feel very real. This is a competitive space, and winning here is going to take a special team, and this group feels like exactly that. Two weeks in, the pace has been intense in the best way. The team moves fast, cares deeply about the product, and with real agency to work across the stack and make things happen. We have some big launches coming soon that I’m excited to share more about. And yes, we’re hiring across the board. Reach out if you’re interested!
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Aameek Singh liked thisAameek Singh liked thisThrough grad school and a couple startups later, Google has stood out to me as the ultimate destination to work at over the last 15 years (a third of my life as a colleague pointed out). It has been at the forefront of most technological shifts over my career, and somehow still balances it with the most incredible friendly and nurturing environment to grow. It's safe to say that many Googlers find within an environment similar to grad school -- interesting problems, multiple billion-user products, clever and quirky coworkers, and a far better stipend! Like a banyan tree spreading its roots to form a canopy, Google technology, people and culture have branched out over the last decade and more to help shape the ecosystem of companies and startups that dot the modern tech industry. So suffice it to say that Google, and Deepmind more recently, have profoundly shaped how I think about work, the world and the people around me. Thank you to all my present and former teammates, Nobel laureates, Turing award winners, and everyone else that have been such powerful inspirers! Now the fun ride continues at Waymo. Onboarding yesterday felt like a blast to the past, getting dizzy on seeing new problems and happy to meet new (and old) friends! p.s. here's a fun take I shared internally to the teams I have been a part of: ------ Burp... that was satisfying 😋 Hey friends! Being a bit of a foodlover lends a fun lens to view my 3-course journey at Google and GDM. Search is synonymous with Google, and being part of its quality and evaluation teams was a wonderful appetizer to get stuck into the heart of what Google has on offer. The mission remains timeless even as the problems have evolved. TTS, Speech, and Gemini Audio formed the main course: from pumping billions of hours of audio waveforms through our TPUs daily, to recreating voices afflicted by ALS, to defining when accents and intonation sound perfect in each of our products. The challenges are profound, yet very human: trying to do something most toddlers master rapidly before they learn to read. And finally, working in GDM evaluating frontier models has been the ideal dessert: intense and sweet (and fleetingly brief). The central challenge of measuring intelligence is like no other, and engages some of the best minds I have met. You all have been the best fellow diners: fun, lively and wicked smart. Thank you for your friendship, generous advice and help, and for teaching me fun things: Google is truly a unique crucible to best experience this. Our stories of launches, turndowns, outages and april fools jokes we've shared and swapped will be the ones I remember. A special gratitude to each of my managers and many mentors for kindly and tirelessly growing me in ways I never foresaw, and whose lessons I continue to learn from. My next meal will be at our sister restaurant next door: Waymo's challenges beckon me to sample a new cuisine. I trust we will dine together again!
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Aameek Singh liked thisAameek Singh liked thisI recently joined the J.P. Morgan “Making Sense” podcast to discuss quantitative investing in commodities and macro markets. We explored themes including: 1) why commodities remain a differentiated source of diversification and alpha 2) how alternative data and scalable research/platform infrastructure are reshaping the investment process 3) the changing client landscape and growing sophistication of investor objectives 4) expansion into newer universes and broader opportunity sets Really enjoyed the conversation with Eloise Goulder.
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Aameek Singh liked thisAameek Singh liked thisBig news: Last week I joined Duolingo as a Senior Engineering Manager! 🦉 After an amazing run at Cash App, I'm trading fintech for language tech. Honestly, the green owl is very persuasive. I've always believed that the best products are the ones people actually come back to every day (sometimes out of love, sometimes out of fear of a streak). Getting to help build that kind of product with such a talented team? Yes please. Excited for the journey ahead. And yes, my Spanish streak is already running.
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Aameek Singh liked thisAameek Singh liked thisGrateful for three decades at IBM. I came to IBM as an intern in the summer of 1995, while I was still finishing my PhD, and I never really left. Somehow, thirty years passed. IBM is where I grew up as an engineer, as a leader and as a person. It is also where my kids grew up while I built my career. I helped build and grow IBM Security with many great teams and clients around the world, and I am proud of what we built together. At the end of April, I will be retiring. I have worked with some of the best people I have ever known. Most folks know me as a hard grader, so that is not something I say lightly. Colleagues, clients and partners across IBM pushed me to be better in ways I did not always expect. I could not have done any of this without my family. They made real work life integration possible for me. There were many times I took business calls from the sidelines of soccer fields so I could still be there for them. Stepping away from this community is not a small thing. IBM has been home for most of my adult life. I am looking forward to celebrating my daughter's wedding in May and then stepping into the next chapter. To everyone at IBM, and to all the clients and partners who trusted me over the years, thank you! It has truly meant a lot to me. #ibmsecurity #ibm
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MD Fazal Mustafa
Heva AI • 12K followers
Something like this never happens in India. You just can't build for 7 years in Stealth here. Raise roughly half a billion, too. You will just get mocked and laughed at, even by the people in the ecosystem. All this is really just possible in the US.
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Jasjeet Singh
Amazon Web Services (AWS) • 5K followers
Thrilled to announce that OpenAI GPT-5.6 Terra and Luna are now live with in-country inference in India through Amazon Bedrock! Requests through the India endpoint are processed entirely on AWS infrastructure within India. This is a big moment for AI in India, and follows our recent announcement that Anthropic Claude will also be available with in-country inference in India through Bedrock in the coming weeks. India's largest enterprises aren't asking if they should deploy frontier AI — they're asking how fast they can get there with the right controls in place. Here's what I think this particular launch unlocks: choice at scale, without compromise. Through a single Amazon Bedrock API, customers now access OpenAI, Anthropic, Amazon Nova, Meta, Mistral, and more, all with in-country inference, all governed by the same security, governance, and compliance controls they already use. No lock-in. The right model for the right workload, and the freedom to switch as the landscape evolves. We have always believe that customers shouldn't have to choose between the best AI and the controls they need. And this launch enables the same! Recent price reductions announced by OpenAI, Luna costs up to 80% less and Terra up to 20% less, pave the way for wide-spread AI adoption in India. For organizations building AI-powered customer applications serving millions daily, or automating complex workflows like KYC and regulatory filings, this brings frontier intelligence within reach of production budgets, not just innovation budgets. From what I'm seeing: the conversation with regulated enterprises in India have fundamentally changed. It's no longer about data residency concerns or compliance blockers — those are solved. It's about which use cases to scale first. Exciting time to be building in India! #AWS #AmazonBedrock #OpenAI #GenerativeAI #AIinIndia #EnterpriseAI Sandeep Dutta Jaime Valles Mark Lewis Luke Anderson Pramod Boga Vatsal Shah Purnima Sahni Mohanty Praveen Sridhar Kiran Jagannath Amit Anshu Rajeev Singh Pankaj Gupta Satinder Singh Manish Rathaur Nishant Mehta Prabhjeet Singh Nitin Bawankule Pragya Misra Neelesh Sadawarte https://lnkd.in/gmkzU2Ff
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Bhushan Muthiyan
Automaton AI Infosystem Pvt… • 8K followers
A hot take on enterprise AI in India: Most companies are not failing at AI because they lack intelligence. They're failing because they lack infrastructure. I speak to CTOs every week. The conversation always follows the same arc: 'We tried building our own AI team. 18 months in, we've got 3 models in dev, 0 in production, and a ₹2 crore burn with nothing to show for it.' This is not a talent problem. It's a platform problem. Building AI infrastructure from scratch in 2026 is like building your own cloud in 2012. The tooling exists. The platforms exist. The pre-built models exist. What you need is the right AI operating system — not an army of engineers reinventing wheels. That's what Automaton AI is building. - 35+ pre-trained models. 10M+ training assets. - A full LLMOps/DLOps lifecycle platform. - On your infrastructure. - Your data. Your control. Enterprise AI doesn't have to be a multi-year project. It can be a 6-week deployment. The question is: are you using the right platform? What's your biggest AI deployment challenge? Let me know in the comments ↓
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Shubham Jindal
Harness • 2K followers
Got a chance to share a few thoughts with Times Techies / The Times of India on where AI systems are heading next. One nuance I find important: the shift is not simply from “AI answering questions” to “AI doing work.” AI agents were already doing useful work: writing code, calling tools, debugging, browsing, summarizing, and automating narrow workflows. The more interesting shift now is from task automation to long-running autonomous work. With models like GPT-6 Astra, the frontier is becoming less about whether a model can use a tool, and more about whether it can stay coherent across a longer horizon: - Can it preserve intent across many steps? - Can it recover from wrong turns? - Can it coordinate subtasks without losing the plot? - Can it use tools safely? - Can it verify that the final outcome is actually correct? That is also why the surrounding system matters so much. For AI to operate reliably in real workflows, it needs the right harness around it: context, tools, permissions, memory, evals, observability, cost controls, and safety boundaries. The model is a huge part of the leap. But the products that make AI truly useful will be the ones that combine stronger models with the right systems around them. Grateful to have contributed a small perspective to this conversation.
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Hrishikesh Dewan
Ziroh Labs • 8K followers
Sudhi Sachdev of AIM interviewed me yesterday about whether we need GPUs. My thesis, and our company's Ziroh Labs, is that you don't need GPUs to solve pressing problems. Not anymore. Yes, you definitely need large GPUs when you are building a very large model to answer anything and everything in the universe for 7 billion people wth varied interests. But the problems AI needs to solve are not universal; they are specific, and they can be easily decentralised to devices or data centres close to users. After all, stable systems are decentralised as much as all things in the natural world. Igneta Dsouza, Ajay Goel Nadiya Syed Priyam Hazarika Vineet Mittal Khumujam Jenish Singh Kompact AI Ziroh Labs https://lnkd.in/g2htsPUy
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Vyas Sekar
Rockfish Data • 6K followers
In recent days, there has been quite a bit of debate around context graphs spurred by a thought-provoking article by Jaya Gupta and Ashu Garg! In our blog (link below in comments), Hui Zhang and I take a "first-principles" look at what the conversation got right and what's missing from a 𝙢𝙖𝙧𝙠𝙚𝙩, 𝙩𝙚𝙘𝙝𝙣𝙤𝙡𝙤𝙜𝙮, 𝙖𝙣𝙙 𝙡𝙤𝙣𝙜 𝙩𝙚𝙧𝙢 𝙚𝙫𝙤𝙡𝙪𝙩𝙞𝙤𝙣𝙖𝙧𝙮 perspective. To truly unlock the potential of future agentic systems, we identify three challenges and opportunities along these lines: 1. Explicitly tackle the needs of *𝗰𝗼𝗻𝘀𝘂𝗺𝗲𝗿-𝗰𝗲𝗻𝘁𝗿𝗶𝗰 𝗮𝗴𝗲𝗻𝘁𝘀* and not just enterprise business automation 2. Create technical foundations for *𝘀𝘁𝗮𝘁𝗲𝗳𝘂𝗹 𝗿𝗲𝗮𝘀𝗼𝗻𝗶𝗻𝗴 𝘀𝘆𝘀𝘁𝗲𝗺𝘀* at scale to model behavioral patterns and trajectories of users, agents, and the interactions. 3. Move beyond trying to mimic human workflows and try to achieve *𝘀𝘂𝗽𝗲𝗿𝗵𝘂𝗺𝗮𝗻 𝗼𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻* or hit the "AlphaGo" moment (i.e., the AI system can generate an action to achieve an optimized outcome unconstrained by human compute/memory/expertise!) Read the blog linked in the comment below and let us know what you think!
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Mark Relph
Amazon Web Services (AWS) • 9K followers
re:Invent Day 1 is done and it was packed! My day began with a roundtable with some of our best partners talking about how we can better help customers migrate and modernize their AI workloads and use cases. Then Priya Arora and I presented on-stage on how Agentic AI is opening opportunities for partners, from ISVs and SIs, to startups. We shared data from our survey we did with BCG showing the trends in customer adoption of AI, focusing on the industries and use cases with the highest momentum. We also uncovered areas where customers need the most help and support as they roll out their agentic use cases. After that I sat down with 3 key partners, grabbed lunch with a few AWS peers I don't get to see often enough, and had a lot of ad hoc hallway meetings. (It's hard to walk 10 feet at re:Invent without seeing someone you know) But my highlight was launching the new AI Competency and Agentic AI categories for partners. I had a chance to join the AWS OnAir team to talk about it. My team was the driving force behind the launch and I'm proud of what this means for our partner community. We spent months listening to partners tell us they needed a way to stand out in customer conversations around agentic AI. The new AI Competency creates three distinct specialization paths. Agentic AI Applications recognizes partners delivering production-ready autonomous systems. Agentic AI Tools validates partners providing the infrastructure and tooling that makes agent development possible. Agentic AI Consulting Services distinguishes partners with proven expertise helping enterprises design, build, and scale agentic deployments. Each path requires demonstrated technical depth and validated customer outcomes, not just certifications or marketing claims. We launched with 60 partners who achieved the AI specialization. That's the highest number of launch partners in any AWS Competency program so far. Partners like Loka, Anthropic, LangChain, and Mission are already proving their ability to deploy AI systems that handle real business processes autonomously. That validation matters when enterprises are making critical technology decisions. Partners achieving these specializations gain access to funding, co-marketing resources, and priority placement in customer engagements. But what matters most is the market differentiation. When customers are evaluating dozens of partners claiming agentic AI expertise, this competency provides a clear signal about who has actually done the work. For enterprises evaluating partners, this competency provides the differentiation signal you need. These partners have solved the hard problems of moving agents from demo to production, from single use case to enterprise platform. The timing matters. Enterprises are moving past whether to deploy agentic AI and into how to do it at scale. Partners with proven expertise become increasingly valuable as deployment complexity increases. That's what makes this competency so important.
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