David Piegaro

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David Piegaro

David Piegaro

@davidpiegaro

US Army Intel Veteran. Ex Banker applying AI to rapidly scale and expand my family’s small children’s entertainment business.

Jersey City, NJ Katılım Kasım 2012
3.8K Takip Edilen736 Takipçiler
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Dwarkesh Patel
Dwarkesh Patel@dwarkesh_sp·
New blackboard lecture w @reinerpope How do chips actually work – starting with basic logic gates, and working up to why GPUs, TPUs, FPGAs, and the human brain each look the way they do. 0:00:00 – Building a multiply-accumulate from logic gates 0:16:20 – Muxes and the cost of data movement 0:25:59 – How systolic arrays work 0:39:00 – Clock cycles and pipeline registers 0:51:40 – FPGAs vs ASICs 1:03:14 – Cache vs scratchpad 1:07:16 – Why CPU cores are much bigger than GPU cores 1:11:49 – Brains vs chips 1:15:22 – A GPU is just a bunch of tiny TPUs Look up Dwarkesh Podcast on YouTube/Spotify/etc to watch. Enjoy!
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David Piegaro
David Piegaro@davidpiegaro·
@TMTLongShort I saw how bad it was and left after less than a year. Worked on a deal where MD didn’t realize blades and vanes were bigger than just aerospace now…..
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Just Another Pod Guy
Just Another Pod Guy@TMTLongShort·
Utility of sellside is dropping like a stone. The whole model needs to be restructured asap. And yes I understand the corp access and bogey angle. Nevertheless. The least they can do is attempt to replicate Citrini and semianalysis. Not holding my breath.
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David Piegaro
David Piegaro@davidpiegaro·
@garrytan How different from search openai models can do natively ?
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Joe Weisenthal
Joe Weisenthal@TheStalwart·
*INTUIT TO CUT 17% OF JOBS TO STREAMLINE OPS, FOCUS ON AI: RTRS
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Alex Imas
Alex Imas@alexolegimas·
I keep coming back to @BenSasse’s comment that I think perfectly captures some of the anxiety around AI (paraphrasing): for a very long time now, you could go to school and decide on a job that you can expect to do for your entire adult life. That era is now over.
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Patrick OShaughnessy
Patrick OShaughnessy@patrick_oshag·
This is my sixth conversation with @GavinSBaker. As always with Gavin, the conversation covers a lot of ground, but we spend the most time on watts and wafers. We discuss: - Why the wafer shortage may prevent an AI bubble - Data centers in space (reframed) - Elon's Terafab and the new chip companies challenging Nvidia - Usage-based pricing - The disaggregation of GPUs - DRAM, frontier tokens, and open source Enjoy! Timestamps: 0:00 Intro 7:55 Anthropic and OpenAI Valuations 12:58 Watts, Wafers, and Infrastructure 14:39 Orbital Compute and Data Centers in Space 22:49 Avoiding the AI Bubble 28:26 Terafab and the Future of US Manufacturing 32:16 Returns to the Frontier 37:23 Continual Learning 42:03 New Chip Companies 48:52 Extending GPU Lifespans and Private Credit 51:22 The Application Layer 57:32 The Token Path and Open-Source Dynamics 1:01:37 Cybersecurity 1:05:46 Diversity Breakdown 1:11:59 Assessing the Big Tech Players in AI 1:19:02 Geopolitics, Personal Safety, and the AI Horizon
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David Piegaro
David Piegaro@davidpiegaro·
@andruyeung Commuting on the ferry and seeing the skyline over the water was always magical, every morning.
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Sam Altman
Sam Altman@sama·
customers are increasingly asking us for certainty on capacity. as models get better, we expect that the world will be capacity-constrained for some time. we are offering discounted tokens for 1-3 year commits. (it also helps us plan, so hopefully a big win-win.)
OpenAI@OpenAI

Introducing OpenAI Guaranteed Capacity: a new offering that enables customers to guarantee long-term access to OpenAI compute. We’ve made long-term investments in infrastructure, partnerships, and capacity planning to help customers scale reliably. Now, Guaranteed Capacity helps customers plan ahead for critical workloads in a compute-constrained world. openai.com/guaranteed-cap…

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Dean W. Ball
Dean W. Ball@deanwball·
I am sufficiently impressed by the AI features and products integrations Google has showed off at I/O today that I am very tempted to buy an Android phone for the first time in 16 years.
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Noam Brown
Noam Brown@polynoamial·
Andrej @karpathy is back in the game! I would have loved for him to rejoin @OpenAI, but I'm happy he's at any frontier lab pushing the field forward. It’s easy to frame this as zero-sum among the labs, but in truth we’re collectively advancing the most important tech of our era.
Andrej Karpathy@karpathy

Personal update: I've joined Anthropic. I think the next few years at the frontier of LLMs will be especially formative. I am very excited to join the team here and get back to R&D. I remain deeply passionate about education and plan to resume my work on it in time.

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Derrick Choi
Derrick Choi@derrickcchoi·
My colleagues wrote up a great post on using Goals in Codex. They go through when to use them, what changes when a Goal is active, and how to write Goals that give Codex a clear outcome, constraints and verification criteria. Also how we designed Goals at the architecture level if you’re curious. developers.openai.com/cookbook/examp…
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David Piegaro
David Piegaro@davidpiegaro·
@austin_rief I’m between South Florida and New York a lot and love them both! Been missing NYC a lot recently though…. Florida is a better arb in the winter!
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Austin Rief ☕️
Austin Rief ☕️@austin_rief·
It feels like everyone I know living in top east coast cities (NYC, Boston, DC, Philly) is either moving to Florida or thinking about moving to Florida.
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Shanu Mathew
Shanu Mathew@ShanuMathew93·
Love the ideas in here. The investment industry is going to evolve quite a bit over the next 5-10 years. I am def thinking about younger roles less as mechanical processing and pure workhorses into creative, AI-augmented data scientists. The companies that survive are going to be the ones that tailor their programs to allow self-exploration and study with these tools but also turbocharge them by streamlining training and educating them on architecture, best practices, etc. I’ve had so much fun paying around with tools and seeing what’s possible. I trade notes with other investors in my personal network but is anyone sharing publicly or in private channels about best practices, opportunities, limitations? There’s enough of us on FinTwit alone. Reach out if you’d be interested in organizing a little group or slack or something. Just thinking out loud
Brett Caughran@FundamentEdge

I was in New York last week and for the first time I'm starting to hear senior investment professionals think seriously about the incremental utility of junior investment talent. Agents are solving process bottlenecks that heretofore required the efforts of junior investment talent across modeling, meeting prep, and data analysis. ”I may not need to hire a junior after all”, It is a more common refrain. And it's widespread enough that I do think some concern is now warranted. My response back is: what if you just fundamentally rethought the role of the junior investor? What if instead of updating models, updating weekly industry data drops, writing first cut earnings previews, and building out management question lists, the responsibility stack of a junior dramatically changed? What if you simply challenged the junior investor to develop more accurate and timely revenue forecasts across three dozen names? And the apprenticeship role almost felt more like an AI enabled data scientist, while that person develops their own investor toolkit. What if you challenged that junior analyst to be an in-house AI-enabled risk analyst? Building AI-augmented risk checklists, counter pitches on every idea in the portfolio & pipeline? What if you challenged that junior to become the most AI-fluent person on the team, putting them through an intensive six-month AI self-study? Which, for your senior investors with portfolio responsibility, is very difficult to find the time. The junior then, through the apprenticeship period, becomes a highly value-added generalist. And during that apprenticeship period, where they're mostly a cost center, they develop into a true AI-augmented investor, and at year three will drive dramatically positive ROI to the firm. Same apprenticeship model, but rethought in specific structure. The foundational reality still exists that your junior investor for a scaled investment firm is going to be a rounding error in terms of comp. The consideration of slowing down junior hiring isn't a cost consideration, it's an efficiency consideration. And while much of the traditional junior stack is quickly becoming abstracted into agents, I do think there is a real potential to rethink the role of junior investors to the effect of very attractive ROI. I do think, to a large degree, we have some moral responsibility to do this as well. In a competitive business, it is absolutely imperative that we drive efficiencies and research quality with all the tools at our disposal. That definitionally will impact the existing role of juniors more than seniors. I'm feeling a bit more of a mission to help firms rethink how they deploy junior talent. If you're doing the same, I'd love to connect and find creative ways to rethink the junior role in fundamental investing firms.

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Dwarkesh Patel
Dwarkesh Patel@dwarkesh_sp·
At one point during covid, California was only managing to get 25% of its vaccines into arms. @patio11 told me about the political jockeying that delayed the vaccine rollout:
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David Piegaro
David Piegaro@davidpiegaro·
@jxnlco Excited to read - would have you on my podcast but NJ themes - so unless you are from NJ... I am trying to get @TheRealAdamG if you want to put in good word
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jason
jason@jxnlco·
jason from the codex team here, heres a draft on codex maxxing and the primatives i use on a daily basis jxnl.github.io/blog/writing/2… would love any feedback
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Kath Korevec
Kath Korevec@simpsoka·
What other Codex papercuts should we fix?
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