Browse entries 1009–1025 of 1025. Return to the first page to search and filter the complete collection.
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Ask any LLM a financial question about your business. You'll get a fluent, confident, generic answer — one that doesn't truly know your business, or what happened when businesses like yours made that same decision. We build financial AI at Intuit serving 100M+ customers.
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In finance a number is worthless until you can say where it came from. Vinoo Ganesh, CEO of Kepler, starts from the fact that language models are probability machines, brilliant at next token prediction and unreliable at the deterministic work, like arithmetic, that finance actually runs on.
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At Palantir, forward deployed started as a literal description: you were deployed, physically, at the customer's site, and the onboarding project was keeping the platform from falling over. Natalie Meurer's dirty secret is that the title never settled after that.
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Look at public software companies and very few ever crack half a million dollars in average contract value, and that gap is where forward deployed engineering lives.
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Type llama into a catalog of 3 million public models and the result still has to feel instant. At 20,000 models any query is fast; at Hugging Face's scale, 14 million users and a million datasets on top, search becomes the hard part.
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Data Quality Research at Prime Intellect and State of Data Author. Prior investor at Hummingbird and Costanoa.
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A generated clip where the character stands frozen for four seconds can still score well, because the judge rewarded the gloss and the vibe instead of what actually happened.
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Every month it is the same trap. A reasoning model gets upgraded at the same price per token, then quietly burns three times the output tokens. Or the new version costs 40% more and deprecates its predecessor in four months. Are you growing 40%? Making three times the revenue?
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By declaring a task's inputs and outputs without initially considering model capability, you create the space needed to determine execution later. DSPy's promise is that AI engineering should happen above a particular prompt template or provider API shape: the Signature.
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Live from San Francisco, AI Engineer World’s Fair 2026 continues with Day 2 of session programming from the main stage. Watch live for keynote sessions, main-stage programming, and more from World’s Fair 2026 as AI Engineer brings another full day of AI engineering content to viewers online.
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Live from San Francisco, AI Engineer World’s Fair 2026 wraps with the final day of main-stage programming. Watch live for keynote sessions, featured talks, and closing-day highlights from World’s Fair 2026 as AI Engineer streams the final day of the event online.
OECD launches a Global Call for Governing with AI, inviting governments to share AI use cases, policy initiatives, and implementation tools to support trustworthy AI in public administration.
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April 20, 2026 - all times in EST -- 9:00am - Welcome to AI Engineer Miami -- 9:10am - Gabe Greenberg, G2i Opening Remarks -- 9:15am - Dax Raad, OpenCode Keynote -- 9:40am - Dexter Horthy.
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AI Engineer session on Buy Now, Maybe Pay Later: Dealing with Prompt-Tax While Staying at the Frontier - Andrew Thomspson. It adds practical context for how teams are building and operating AI systems in production.
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A single spatial biology run can yield two to six terabytes of data, far more than a scientist can eyeball, and Kenny Workman argues that this is the raw material for teaching AI to actually do science.
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RLHF made models that are extraordinary at pleasing the human in the loop, and Diogo Almeida, a GPT-4 co author, argues that is exactly the problem.
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The old story is that a base model is a mirror of the internet, a good model of human web text that everything else gets bolted onto. Varun Singh, who leads pre-training at Arcee AI, argues that story is dead: no modern base model reflects the web the way GPT-3 once did.