distributed training & rl @simplismartHQ, soccer u19 cap, rl envs. 21. dms open.

Joined April 2022
96 Photos and videos
Pinned Tweet
28 May 2025
had just shipped a repo for training speculative decoding heads to speed up inference of llms by ~3x. get any base model, train a few speculative heads, see the difference in throughput. 🧵on more details. 1/n
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Harshith retweeted
Sandboxes are all the rage (Modal, E2B, AWS, ..). Most AI teams pay a >4x markup to run sandboxes on someone else's machines. Introducing SkyPilot Sandboxes — Run BYOC sandboxes on your own clusters. • 50,000 sandboxes on a single cluster • Sub-second launches with warm pools • Great for RL rollout (keep sandbox clusters close to GPUs) Benchmark shows @skypilot_org Sandboxes are 4-10x cheaper than Modal at lower latency. Full results in blog.
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Harshith retweeted
šŸš€ We're excited to be a Day-0 launch partner for NVIDIA Nemotron 3 Ultra. Deploy NVIDIA's latest open model for agentic AI on Simplismart Our optimizations we deliver higher throughput than TensorRT MTP NVFP4. Read more: lnkd.in/g7BrrNhy #NVIDIA #Nemotron
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Harshith retweeted
the secret to great writing is to use witty instead of funny, clarity instead of complexity and claude instead of chatgpt
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nothing. i repeat nothing will stay the same as we know. think about this - products like salesforce, etc are used by a very minute margin of people and has a market cap of $150B, think of all the experiences that could be possible through innovations like this. endless honestly. gaming and content will converge, and world models will give us the claude-code type growth but for the rest of the distribution curve. i dont think we know whats coming, honeslty nobody does. we are histroy in the making damn.
May 18
Excited to share that we’ve raised $300M in our Series B round, led by @radicalvcfund, bringing our total funding to more than $450M, with leading technology companies joining as both customers and investors. We continue accelerating the path to AGI through our two core pillars: ultra-optimized infrastructure for AI workloads, and realtime world models built on top of it. Today, we’re also launching DOS (Decart Optimization Stack) 2.0 – our next-generation inference and training platform, delivering over 1,600 tokens per second for agentic inference and over 100 FPS for world models across major hardware platforms. Alongside DOS, we will launch new versions of our world models in the coming weeks: Lucy, for immersive realtime experiences, and Oasis, for physical AI. Grateful to our partners, customers, and backers across media & entertainment, Physical AI, chips, hyperscalers, and the broader AI ecosystem. @radicalvcfund, @Adobe, @alphaptrs, @amazon and @awscloud, @Atreidesmgmt, @benchmark, @eBay, @nvidia, @sequoia, @Toyota, @valor, @orenzeev; Andrej Karpathy, Michael Eisner, Yamauchi-No.10 Family Office, Moritz Baier-Lentz and more. We made a film for this moment with Decart CEO @DLeitersdorf and Moritz Baier-Lentz - a look at the company, the technology, and what comes next.
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Harshith retweeted
/goal build GTA 6 Is this the AGI test? One prompt in -> full playable game out? How good can a single prompt get? gta6-single-prompt.vercel.ap…
fine, i'll do it myself
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i think it was @Suhail's post recently, where he said a good vector to have your company in is: is every new release by big token is a net scare or insane boost of your product/ service offering. just saw claude agents view and it seems like it's over for companies like conductor etc. you just cannot exist in the path of big token. time to get back to hard engineering problems.
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welcome to the physical era.
May 17
The moment the robot passed the human worker, because the human had to take a bathroom break
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Harshith retweeted
This is rapidly becoming the greatest product demo since Steve Jobs’ ā€œone more thingā€. Congratulations folks, you have just exited the smartphone era. Welcome to the robot era. May you live in interesting times.
We got bored. Time for Man vs. Machine x.com/i/broadcasts/1qGvvkQMg…
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idk mate, i just solve problems, release and speak to my client cus they don't know what they want. call me what you want now.
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Harshith retweeted
If you are 22-25 years old (or any age!) here is evergreen advice that will never lead you wrong: 1) all deep meaning in life comes from being part of a team. As long as you bias your career and life choices toward the question ā€œwhat is the best team (environment) for me?ā€ you can’t go wrong. Humans evolved to work in a pack. And once you are with an ā€œApex packā€ you can’t ever be in a non-Apex pack again. This is why so many elite athletes fall on hard times after retirement. Find your elite pack. 2) find something you enjoy doing that especially brings you intellectually curiosity or wonder. Apex packs are basically filled with those types. A sense of wonder unlocks all. So don’t try to reverse engineer how these people ā€œmade it.ā€ Just stay true to how humanity as a whole ā€œmade it.ā€
May 16
The vibes in SF feel pretty frenetic right now. The divide in outcomes is the worst I've ever seen. Over the last 5yrs, a group of ~10k people - employees at Anthropic, OpenAI, xAI, Nvidia, Meta TBD, founders - have hit retirement wealth of well above $20M (back of the envelope AI estimation). Everyone outside that group feels like they can work their well-paying (but <$500k) job for their whole life and never get there. Worse yet, layoffs are in full swing. Many software engineers feel like their life's skill is no longer useful. The day to day role of most jobs has changed overnight with AI. As a result, 1. The corporate ladder looks like the wrong building to climb. Everyone's trying to align with a new set of career "paths": should I be a founder? Is it too late to join Anthropic / OpenAI? should I get into AI? what company stock will 10x next? People are demanding higher salaries and switching jobs more and more. 2. There’s a deep malaise about work (and its future). Why even work at all for ā€œpeanutsā€? Will my job even exist in a few years? Many feel helpless. You hear the ā€œpermanent underclassā€ conversation a lot, esp from young people. It's hard to focus on doing good work when you think "man, if I joined Anthropic 2yrs ago, I could retire" 3. The mid to late middle managers feel paralyzed. Many have families and don't feel like they have the energy or network to just "start a company". They don't particularly have any AI skills. They see the writing on the wall: middle management is being hollowed out in many companies. 4. The rich aren’t particularly happy either. No one is shedding tears for them (and rightfully so). But those who have "made it" experience a profound lack of purpose too. Some have gone from <$150k to >$50M in a few years with no ramp. It flips your life plans upside down. For some, comparison is the thief of joy. For some, they escape to NYC to "live life". For others still, they start companies "just cuz", often to win status points. They never imagined that by age 30, they'd be set. I once asked a post-economic founder friend why they didn't just sell the co and they said "and do what? right now, everyone wants to talk to me. if i sell, I will only have money." I understand that many reading this scoff at the champagne problems of the valley. Society is warped in this tech bubble. What is often well-off anywhere else in the world is bang average here. Unlike many other places, tenure, intelligence and hard work can be loosely correlated with outcomes in the Bay. Living through a societally transformative gold rush in that environment can be paralyzing. "Am I in the right place? Should I move? Is there time still left? Am I gonna make it?" It psychologically torments many who have moved here in search of "success". Ironically, a frequent side effect of this torment is to spin up the very products making everyone rich in hopes that you too can vibecode your path to economic enlightenment.
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such good research taste from tml. from tinker to this. imagine how many things this opens up to. i can finally learn to use cad in a fun interactive way. next few years will look nothing like now. our kids will laugh on the fact that we got hyped up by cli interfaces.
Today we're sharing our work on interaction models. A new class of model trained from scratch to handle real-time interaction natively, instead of gluing it onto a turn-based one. youtu.be/A12AVongNN4
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Harshith retweeted
Replying to @AnziParazzi
Backpropaganda
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Harshith retweeted
Today we introduce Physera, a research and product lab rethinking applied intelligence. We are working at the intersection of model efficiency and behavioural simulations while building environments that are multimodal. We are a team of applied researchers and engineers who believe that the important problems in AI today are not about capability but making that capability reliably useful across multimodality. We are heads down building systems that perceive, reason, and decide as humans do, under the constraints humans face. To learn more or collaborate: physera.ai/?v
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Harshith retweeted
if you're ever in doubt whether to apply to that fellowship, that job, or asking someone out. just know that Aidan Gomez once applied to a Grad role at Google Brain as an undergad, the recruiter missed he was an undergrad and he ended up co-authoring the paper "attention is all you need" off of a clerical mistake. @aidangomez correct me if i am wrong but i find it truly one of the wildest examples of "you miss 100% of the shots you don't take" source: an interview of aidan gomez i watched a year back
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guys don't understand why you babe. also guys:
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guys don't understand you babe*
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"can we give them the confette, they are genzs they need it." 😭😭😭
At Stripe Sessions, we showed how we think agentic commerce will often happen behind the scenes in the course of producing other final products. Here, we show our Claude Code using MPP and @tempo to buy a dataset from @alpha_vantage in the process of generating a research report for me on AI energy usage.
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its gonna snow next in blore.
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Harshith retweeted
Did a very different format with @reinerpope – a blackboard lecture where he walks through how frontier LLMs are trained and served. It's shocking how much you can deduce about what the labs are doing from a handful of equations, public API prices, and some chalk. It’s a bit technical, but I encourage you to hang in there - it’s really worth it. There are less than a handful of people who understand the full stack of AI, from chip design to model architecture, as well as Reiner. It was a real delight to learn from him. Recommend watching this one on YouTube so you can see the chalkboard. 0:00:00 – How batch size affects token cost and speed 0:31:59 – How MoE models are laid out across GPU racks 0:47:02 – How pipeline parallelism spreads model layers across racks 1:03:27 – Why Ilya said, ā€œAs we now know, pipelining is not wise.ā€ 1:18:49 – Because of RL, models may be 100x over-trained beyond Chinchilla-optimal 1:32:52 – Deducing long context memory costs from API pricing 2:03:52 – Convergent evolution between neural nets and cryptography
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i don't know which is a bigger crime - accessing mythos without ant's approval or using mythos for creating websites.
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