AI Analyst at GAI Insights. Follow for latest insights on GenAI.

Joined July 2011
Ankaj Mohindroo retweeted
Ashish Kacholia has warned that the market may turn Bearish due to rising interest rates. U.S. FED raised rate by 25 bps. RBI followed & raised repo from 5.25% to 5.50%. Experts say RBI needs to raise repo to at least 6.25%. This will hit corporate profits & derate risky assets.
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Ankaj Mohindroo retweeted
Introducing Gemini 4 Argon, our new frontier model, rolling out to cyber defenders starting today, and more widely as soon as possible. I am really excited by the progress we have made here. Argon is priced at $2 in and $10 out during introductory pricing!
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Ankaj Mohindroo retweeted
openai announces glm-5.3 in codex subscriptions anthropic announces glm-5.3 is evil and chinese
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Ankaj Mohindroo retweeted
After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI? I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev • 20-200x faster • 40-400x cheaper (w/ output tokens free) • Frontier composable intelligence optimized for decisions AFAICT the shortest path to AI-based economic revolution
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Ankaj Mohindroo retweeted
This week brought some of the clearest statements we've heard from both Anthropic & OpenAI that some form of recursive self-improvement has been achieved, though it still sounds early RSI will cause rapid gain in AI ability & the first firms to RSI may get an unsurmountable lead
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🎙️Full tech report on how to actually achieve SovereignAI, from data to model training, values, infrastructure, to large-scale deep research. Bridging up to 7 months of Frontier AI development with a $450k training Continual Learning run 🧠 📜 Paper: tinyurl.com/yk347xb 💻Model: tinyurl.com/2ju6z7dc Partners: @imperialcollege, @datologyai, @LambdaAPI
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Ankaj Mohindroo retweeted
Replying to @_sholtodouglas
Sholto, thank you for setting the record straight. Larger issue is that multiple very serious people in Silicon Valley have heard some variation of this and believe it to be true. And the reason it is believable to so many is that it is consistent with Dario’s public messaging and what he outlined in the essay you shared: this technology *might* be dangerous for humans in multiple ways, could lead to extreme concentration of economic power (as outlined in the essay) and therefore needs to be regulated thoughtfully. I agree with the potential risks and I believe Dario makes all of these arguments in good faith. 
As discussed on the pod, if one agrees that AI *might* be dangerous, there are two ways to address this potential risk. Either concentrate it in the hands of a chosen few companies and politicians via regulation or distribute it widely. Essentially boils down to whether one believes AI is too dangerous to concentrate or too dangerous to distribute. There are reasonable arguments on both sides, but I profoundly agree with Zuckerberg’s statement that: “The notion that AI is so dangerous that the only safe path is an extreme concentration of power seems inherently problematic. Historically, hoping that an absolute power will benevolently provide for humanity if sufficiently enlightened has not led to safe or positive outcomes.” And as Dario says in the aforementioned essay, “some may object that we can simply keep AIs in check with a balance of power between many AI systems, as we do with humans.” I believe this is the best path forward: I want as many AIs as possible to maximize the odds that one shares my own particular values. And as Dario notes, no human has ever been able to take over the world. At this point, I think safe to say that Dario has lost the argument. His messaging has failed to result in his preferred regulatory path. The fact that the only solution to the recent incident where an unreleased advanced OpenAI model hacked Hugging Face was an open-source model likely ended any chance of strict near-term regulation. Essentially every major company other than Anthropic has signed Jensen’s letter. However, Dario’s messaging has been massively helpful to efforts to ban datacenters here in America. I suspect we will see anti-datacenter advocacy groups runnings ads using clips of Dario warning about how dangerous AI could be for humans. His good faith efforts in favor of regulation are now increasing the odds that AI will not be beneficial for Americans and humans everywhere. I believe that there is a reasonable chance AI might help us cure most forms of disease such that we have extended lifespans and can enjoy these long lives in an abundant Star Trek like future. That is the future that I want and I think Dario is decreasing the odds of that future at this point. He is about to be the CEO of one of the most important public companies in the world and given that the pro-regulatory effort has failed (at least for now), I respectfully think he should make an effort to be a more positive advocate for his own industry. And if I am wrong and we do need to regulate this technology, he will be a more effective advocate for this in the future having been open-minded to the alternative. And for the sake of clarity and as I outlined on the pod, I think Anthropic has deep competitive advantages and is an amazing company. Ironically, the main risk I saw to Anthropic a few months ago was nationalization as a result of Dario’s own rhetoric and behavior.
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Ankaj Mohindroo retweeted
GAI WORLD 2026: WHERE AI ENTERPRISE LEADERS ARE LEARNERS Enterprise Transformation Starts with Leaders Willing to Learn For a preview of the learning that takes place at GAI World 2026, register for tonight's GAI Insights Learning Lab Link to register: luma.com/todadwqk Every organization says they want transformation. But transformation only happens when leaders are willing to challenge old assumptions, rethink how work gets done, and learn faster than the pace of disruption around them. 📍 GAI World 2026 | Boston AI Week 📅 September 28–30, 2026 🎟️ Enterprise registration is now open: gaiworld.com?utm_source=link… #GAIWorld2026 #EnterpriseTransformation #AILeadership #EnterpriseAI @amhrtech @PaulBaier @jjsviokla
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Ankaj Mohindroo retweeted
Dozens of enterprise AI platforms are competing for your budget right now. Every vendor claims to be the leader, and most buyers cannot tell them apart. On July 6, we fix that. Ankaj Mohindroo, our Head of AI Research, leads a free Learning Lab on moving from scattered pilots to AI at scale. He will break down the three decisions that matter most: vendor selection, contractual terms, and architecture. Andy Roberts from Microsoft joins to map where Microsoft fits. Free. Live online. July 6, 7:00 PM ET. Save your seat 👉 luma.com/todadwqk @amhrtech @PaulBaier @jjsviokla
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Ankaj Mohindroo retweeted
Stop guessing your AI strategy and start making data-driven decisions. Join us for our next free Learning Lab on Monday, July 6, at 7:00 p.m. ET for an exclusive deep dive into the enterprise AI landscape featuring: Ankaj Mohindroo: Walking through the 4th edition of our Corporate Buyers' Guide to Enterprise AI Platforms. We’ve spent dozens of hours evaluating vendors, including NDA-level briefings, to rate the market and identify critical missing terms in AI contracts. Andy Roberts (Data Platform and AI Architect, Microsoft): Providing an essential overview of Microsoft AI offerings to help you navigate their ecosystem. We will cover the impending "token explosion," evaluate vendor profiles, and highlight which platforms have active, public customers. 👉 Register now: luma.com/todadwqk #EnterpriseAI #MicrosoftAI #AIBuyersGuide #GAIInsights #LearningLab @PaulBaier @jjsviokla @amhrtech
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Ankaj Mohindroo retweeted
The AI demo shows what is possible. The SLA shows what is promised. Before signing an enterprise AI contract, look closely at uptime, service credits, support, and model deprecation terms. The SLA is part of the product. Full comparison in the GAI Insights Q3 2026 Buyer’s Guide: gaiinsights.com/cbg-llms @amhrtech @PaulBaier @jjsviokla
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Ankaj Mohindroo retweeted
have been thinking a bunch about model routing and related things current thoughts here, would love feedback: 1/ there is a difference between "model routing" and "model council" "model routing" = route to one best model. i think only real reason to do this is cost "model council" = pass to many models at the same time, then aggregate responses. this is done to push frontier performance 2/ "model council" seems to be having a moment recent. @OpenRouter did their Fusion thing, @SakanaAILabs did fugu I do think there are use cases where this can be useful - @nlarusstone highlights how they use it for tough bio problems and the most recent "max agency" i'm unsure how you would use it to drive a main agent, but as a "tool" makes sense. similar to how anthropic's advisor tool 3/ model routing in theory sounds nice and im probably a bit more bullish that dax. I dont think expecting ALL users to be on top of which model to use when is feasible. (maybe for coding its more feasible, im thinking broader tho). prompt caching is a real concern. maybe you can heavily bias towards not switching once its been routed once initially? 4/ main reason for model routing is cost. but there are probably other (simpler) levers to pull first. eg putting spending caps, maybe on a per model basis (you get X dollars for opus, then need to use sonnet) at langchain we are doing (4) first (basic cost controls/policies: langchain.com/blog/how-we-ma…) but considering routing and other options
i have low conviction on model routers - very open to changing my mind but this is a snapshot of my current thoughts - i don't think it's good to not be aware of what model you're using. coding with LLMs is a skill you develop and getting a feel for models is part of that - people (at scale) don't have this skill right now which is why a lot of companies are complaining that people are using expensive models for dumb things. a model router promises to solve this without the user having to do anything but i think the issue is missing feedback loops to the user. id rather we figure out how to help users get smarter - i dont even know how much you can model route when factoring in things like prompt cache. only so much you can do - their effectiveness is a bit exaggerated by the same dynamic that's impacting everything AI. so many companies desperately searching for opportunities and trying anything. model routing is the one thing models labs cannot do so everyone is jumping on it
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Ankaj Mohindroo retweeted
Many companies are not scaling AI yet. They are scaling pilots. Different teams, different models, different workflows, and no shared way to measure what is actually working. That matters because the vendor stack you need for early experimentation is very different from the one you need for orchestration, agents, and AI-native workflows. That is why we built RISE, our maturity framework for enterprise AI adoption. We cover it in the GAI Insights Q3 2026 Buyer’s Guide. Visit gaiinsights.com/cbg-llms for more info. @amhrtech @PaulBaier @jjsviokla
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Ankaj Mohindroo retweeted
Why demand is growing so fast: More compute + more data → better AI. Better AI → more usage. More usage → more data and compute demand. Repeat. AI is the first technology that creates demand for itself.
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Ankaj Mohindroo retweeted
The hidden cost of AI is not the build. It is the upkeep. When a vendor changes or deprecates a model, the work does not stop at switching endpoints. Teams have to retest prompts, revalidate workflows, and make sure customer-facing outputs still behave the way the business expects. That takes time, budget, and ownership. AI systems are not “set and forget.” They need a maintenance plan from day one. Visit gaiinsights.com/cbg-llms for more information. We cover what buyers should budget for in the GAI Insights Q3 2026 Buyer’s Guide. @amhrtech @PaulBaier @jjsviokla
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Ankaj Mohindroo retweeted
AI is quickly becoming one of those areas where early choices can have long-term consequences. It’s not just about whether a company is using AI. It’s about which models they trust, how they deploy them, which vendors they build around, and whether the stack can actually scale with the business. That’s why we evaluated 30 AI vendors in the GAI Insights Q3 2026 Buyer’s Guide. Visit gaiinsights.com/cbg-llms for more details The companies that get this right will not just adopt AI faster. They’ll build on a stronger foundation. #GAIInsights #BuyersGuide @amhrtech @PaulBaier @jjsviokla
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Ankaj Mohindroo retweeted
Fable 5 is state-of-the-art on nearly all tested benchmarks, with exceptional performance in software engineering, knowledge work, scientific research, and vision. The longer and more complex the task, the larger Fable 5’s lead over our other models.
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Ankaj Mohindroo retweeted
Introducing Claude Fable 5: a Mythos-class model that we’ve made safe for general use. Its capabilities exceed those of any model we’ve ever made generally available.
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Ankaj Mohindroo retweeted
Replying to @AaronLCannon
🤣🎯
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