Lonne Jaffe

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Lonne Jaffe

Lonne Jaffe

@lonnej

MD @insightpartners | ex-CEO @PreciselyData

New York, NY Katılım Kasım 2008
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Lonne Jaffe
Lonne Jaffe@lonnej·
the replay of my keynote at our @scaleupevent - I divide things into three time phases, and in that context talk about the foundation model landscape, elasticity of demand, consumer surplus, incumbents integrating generative AI features, the potential for switching costs eroding for legacy products, products and business models that could become obsolete, threshold effects as AI systems pass human performance at various tasks, the "wall" and whether AI models will start improving more slowly, among other topics. @insightpartners @CentralReach @quantummetric @FeaturespaceLtd @runailabs @OpenAI @GoogleDeepMind @AnthropicAI @xai @GliaInc
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Eliezer Yudkowsky
Eliezer Yudkowsky@allTheYud·
TIL that Gemini, Claude, and ChatGPT (but not Grok) are told that today is March 32nd, because if you tell LLMs it's April 1st, the conditional text predictions downstream become less reliable for obvious training-dataset reasons.
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Sourish Jasti
Sourish Jasti@SourishJasti·
1/ The future of general-purpose robotics will be decided by one major question: which flavor of data scales reasoning? Every major lab represents a different bet. Over the past 3 months, @adam_patni, @vriishin, and I read the core research papers, spoke with staff at the major labs, and mapped the talent pool. This has completely changed how we think about general-purpose robotics. Our paper builds intuition, step-by step, across the 2025 frontier: from architectures → evals → data → industry dynamics. Each layer reveals a different bottleneck, but they all converge on one truth—data decides everything. Our takeaways + process below👇 If you want access to our graph (sound on), comment or DM me
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Insight Partners
Insight Partners@insightpartners·
AI agents are redefining productivity. Physical agents will redefine labor. In our latest POV, Managing Director Lonne Jaffe, Adithya Sanjay, and Sourish Jasti unpack how robotics is moving from the lab to the real world — delivering ROI across logistics, security, agtech, and more. insightpartners.com/ideas/the-stat…
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dbt
dbt@getdbt·
“Do you love this product?” 0% say yes. 0% switch. On the latest Analytics Engineering Podcast, @jthandy and Lonne Jaffe of @insightpartners unpack why legacy tools stick—and what AI might finally change. 🎧 Listen: getdbt.com/blog/the-histo…
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Lonne Jaffe
Lonne Jaffe@lonnej·
the replay of my keynote at our ScaleUp:AI event just posted to YouTube: youtube.com/watch?v=TZJeSW… -- I talk about the foundation model landscape, elasticity of demand, consumer surplus, incumbents integrating generative AI features, the potential for switching costs eroding for legacy products, products and business models that could become obsolete, threshold effects as AI systems pass human performance at various tasks, the recent discussion around a "wall" and whether AI models will start improving more slowly, among other topics. @insightpartners @CentralReach @quantummetric @FeaturespaceLtd @runailabs @OpenAI @ChatGPTapp @GoogleDeepMind @AnthropicAI @xai @GliaInc
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Lonne Jaffe
Lonne Jaffe@lonnej·
youtu.be/lD6Bcqf0I0U - replay of my 52 min discussion today "Investor’s POV: Mapping the Applied Generative AI Landscape" with @JennaZerker and @PraveenAkkiraju, is up on YouTube, covering (with timestamps): 6:29 – Insight has been investing in AI for countless years, but with the rapid innovation taking place, how do you see the current AI landscape evolving?  12:55 – Where do you think value will accrue across the generative AI stack?  19:05 – What are some examples of how you are seeing “big tech” and portfolio companies incorporate generative AI products and tools?  31:25 – Given how quickly one can “spin up” a generative AI company, how do you think about product defensibility, the concept of moats, and the potential first-mover advantages/disadvantages?  37:36 – How do you manage AI responsibly? What advice do you have for founders on how to build in data privacy, governance, and AI responsibility guardrails?   42:54 – What are some of the “unknowns” or debates you are seeing in the AI community? @insightpartners @swimm_io @OpenAI @weights_biases @runailabs @midjourney_ai @OverjetDental @UnlearnAI @nvidia @IterativeHealth @SingleStoreDB @ProfluentBio @Workato @bardeenai
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Lonne Jaffe
Lonne Jaffe@lonnej·
deepmind.com/blog/alphadev-… "...AlphaDev not only found faster algorithms, but also uncovered novel approaches. Its sorting algorithms contain new sequences of instructions that save a single instruction each time they’re applied. This can have a huge impact as these algorithms are used trillions of times a day. We call these ‘AlphaDev swap and copy moves’. This novel approach is reminiscent of AlphaGo’s ‘move 37’ – a counterintuitive play that stunned onlookers and led to the defeat of a legendary Go player. With the swap and copy move, AlphaDev skips over a step to connect items in a way that looks like a mistake but is actually a shortcut. This shows AlphaDev’s ability to uncover original solutions and challenges the way we think about how to improve computer science algorithms..."
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