Infra marketing @a16z. BASE, @docker, HDP alum. Bay Area born and raised. Everything tech and pop culture. Tweets are my own.

Silicon Valley
Joined July 2009
Deeply technical teams win in AI. Proud to work alongside the @a16z Infra team
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Michelle Lazzar retweeted
This new video model from @fal x @bfl_ai is remarkable. All of these clips were text-to-video, generated in <10 seconds (22x faster than Seedance 2.5 🤯). AI video no longer needs to be painfully slow and expensive. We're entering a new era!
Introducing FLUX 3 Max, the latest post-trained video model from fal Research in partnership with @bfl_ai. FLUX 3 Max is tied for #1 in image-to-video quality on independent third-party benchmarks, generating a 10-second, 720/768p video in ~12 seconds. For the next three weeks, FLUX 3 Max is 75% off, making it the most affordable frontier video model at its quality level.
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if you are getting married and live in SF, don't even think about gifting your partner jewelry or home furnishings
Chinese bride gifts her partner a flagship GPU at wedding — he breaks down in tears She handed him an ASUS ROG Astral RTX 5090 that costs around $12,000
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it's growth engineering. it's taste. it's storytelling. it's new media. it's devrel. it's GTM. it's comms. it's culture. it's narrative. it's marketing.
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this is what i mean when i say things happen on the TL first
Mark Zuckerberg becomes a viral meme after taking an awkward sip of Guinness. 🔗 on.wsj.com/4ynRZrX
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sound on
AI video has gotten SO good - but the sound often doesn't pass the Turing test. Many models generate unnecessary music, exaggerated sound effects, or audio not grounded in the scene. @MireloAI's new SFX model fixes this! You get realistic audio while preserving speech 👇
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first time hearing the job title viceroy of variance
MakerMaker.AI co-founders Dhaval Adjodah and Owen He with a16z's Martin Casado on recursive self-improvement, and how to tell when it's real: A lot of RSI pitches are really just people using AI to build better AI. Tech has always worked that way. You needed computers to build chips. Steam engines got better once you could get coal faster. Dhaval and Owen's bar is higher. The model has to improve itself: its weights, its harness, even the prompt that tells it what to work on next. And the gains have to hold up when you count what they cost. They track everyone's experiment spend on a "bleeder board," and one engineer, the Viceroy of Variance, has the job of breaking their results. Over the past few months, they've started seeing early signs of their system getting better and cheaper at the same time. 0:55 Why most RSI pitches miss 2:25 Optimizer vs. optimizee 5:10 The RSI equation: performance over cost 6:50 Why a closed loop does not mean takeoff 8:40 Humans are agents inside the system too 9:25 The denominator trap: progress divided by capital raised 11:40 Training GPT-2 for $100 13:40 Most RSI papers fail when replicated 16:40 Why you have to co-optimize 17:40 Why inference is the first problem 20:15 The agent rewrites its own prompt 22:20 "It's not a belief. It's happening." 25:00 Why they haven't published 27:50 Intelligence is a vector and Amdahl's law 29:45 The garden hose theory of RSI YouTube: youtu.be/3Q1mdn5ZGvM @makermaker_ai @_dval_ @martin_casado
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i have seen the nice pantry and can confirm. they also have sick fish tanks
Everyone wants to tell me how great their office pantry is but after the Bloomberg pantry nothing can surprise me. The Bloomberg pantry is the size of a small regional airport. The Bloomberg pantry has a fresh peanut butter machine and matcha on tap. The Bloomberg pantry makes the Thrive Capital pantry look positively soviet. Its memory will drive you to tears whenever you visit another newsroom
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Michelle Lazzar retweeted
"The era of software being over, is so over". Hell yeah. Whatever problems humanity must face, computers and software will be central to the solution. So very excited to partner with @CompleteSkeptic and team to make software better. Long devs, long programming and long Jev!!!
launched a model accidentally served trillions of tokens a day 29.4% of the fortune 500 showed up raised a really big series A from @a16z it's been 3 weeks we would like to sleep now
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tired: SaaSpocalypse wired: SaaSpalooza software is so back @CompleteSkeptic @typesafeai
launched a model accidentally served trillions of tokens a day 29.4% of the fortune 500 showed up raised a really big series A from @a16z it's been 3 weeks we would like to sleep now
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please @venturetwins give your take on what models they used. the people want your review!
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Michelle Lazzar retweeted
So excited to back Jennifer Zhou and Ning Cao at @preferencemodel They’re open-sourcing Karotte today, the framework they've used to build RL environments for frontier labs. These RL envs live or die on graders models relentlessly try to game, so Karotte bakes in defenses hardened over 1M eval runs to keep models focused on real tasks instead of loopholes. Preference Model’s target is ML engineering itself, the hardest domain to build envs for and the one every lab wants. Models building models starts here. Shoutout to @Mascobot who was a great partner on this one @chem_safety @Ning_Catsnail
Today we are open-sourcing 🥕Karotte, our framework for building RL environments. We've used it for the past year to build MLE RL environments for frontier labs, and it's been hardened through 1M+ evaluation runs and red-teaming.
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Michelle Lazzar retweeted
Ben Affleck do you use uv?
Ben Affleck reveals he writes Python, understands convolutional neural networks, worked extensively with GPUs, and used his celebrity status to get private looks at Google and OpenAI’s video models “I’ve always been kind of into computers since I was young. Then, when film started to move from analog film to digital, I became more interested in that aspect of it. The visual-effects workflow for many years has included machine learning, so I can write pretty shitty Python scripts and stuff like that. “With convolutional neural networks, which were the precursors to what the transformer can do, which is much more computation simultaneously, you would do things like look at what’s called a tensor. That’s the numerical translation of a visual image in numbers, like the batch number, the frame number and the red, green and blue values of each pixel in each frame. It’s just that simple. That numeric is called a tensor. “You’d use a convolutional neural network to identify patterns that reveal what’s called edge detection or feature extraction, which is identifying patterns well enough to know, this is where the window ledge is, so we can more easily take the green-screen image out and replace it with something. “That was familiar to me early on because, prior to Artists Equity, I had a small visual-effects company. I’ve worked with GPUs a lot too. The visual-effects guys said, ‘Hey, you should see. There are a couple: Google and this other company, OpenAI, are doing really interesting stuff with transformers in video.’ “I’ve learned that I can actually just call up and go, ‘Hey, it’s Ben Affleck. Can I come see what you’re doing?’ Sometimes people say yes, to my astonishment.”
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ty @MistralAI for giving us a reason to bless the TL with Chonkers
Meet Mistral Large 4, aka Le Chonk. • 1T parameters, natively multimodal. 49B active. It is the best open weights model from US or Europe on aggregated benchmarks. • State-of-the-art on critical workloads, including cyber defense, manufacturing and finance and it surpasses closed frontier models on visual grounding. • Forged in Europe end-to-end and is deployable from Europe via our own Mistral Cloud infrastructure. • Available to all via API today. Working with cybersecurity partners privately. Open weights release end of October.
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Michelle Lazzar retweeted
Karpathy: disappears from X 
Ben Affleck: alright, gather round, so you'll want to freeze the base weights first, learning rate 2e-4
Ben Affleck (Hollywood star & Artists Equity CEO) talks about how he fine-tunes open video models by unfreezing weights and trained only the last cinematic layer so a film crew can hit real production standards. for context, Ben Affleck founded InterPositive in 2022, a 16-person AI shop for film post and Netflix bought it in March 2026 for $587 mn in cash. He needed that model because public video models were trained on his peers' films, and he did not think that was a real business. So InterPositive raised money, shot its own dataset for 8 months on a controlled stage, and used it only as late-stage training. Each new film then trains a private model on its own dailies, so the production keeps the footage and the learning. That is the product Netflix paid $587 million for. ---- From "Bloomberg Live" YouTube channel, (link in comment)
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Michelle Lazzar retweeted
Today we’re launching doxx.net, enabling Agentic Defined Networking for everyone. We raised $38M from @a16z, @AnimoVentures and Focal.vc. Create private networks for you and your AI agents, without a server in the middle. 38M+ threats blocked since December. Our first private-network call was a freedom call. Now it’s your turn.
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gm i wonder what fun surprises X dot com has in store for us today
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i can assure you that @YODELAGARZA will be an excellent X follow. he is the guy you want to sit next to at the holiday party to hear some unmatched stories
First day on Twitter! Thank god there isn't a ton of VC drama today.
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holy editing 🤯
Introducing Ideogram 4.5, the most precise edit model. With each edit, leading models add artifacts, pixel shifts, and color changes. Ideogram 4.5 eliminates artifact buildup, making multi-turn editing possible. Live in Ideogram, the API, and launch partners. Open weights soon.
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🐐
Cursor OpenRouter World Labs All in the last few months. @martin_casado and Infra team are truly special.
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