ContentPosts from @itsmekalyani6..
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@faun shared a link, 6 months, 2 weeks ago
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Human coders are still better than LLMs

Antirez recounted a story of working on Vector Sets for Redis, detailing a bug he encountered and his process of finding a solution through a creative approach involving LLM. He explored different methods to ensure link reciprocity and proposed a hashing solution that offered a balance between effic.. read more  

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@faun shared a link, 6 months, 2 weeks ago
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Peer Programming with LLMs, For Senior+ Engineers

LLMs—the mysterious, fickle companions of coding.Senior engineerswade through it, extracting gold with tricks like "Second opinion" and "Throwaway debugging." Seth Godin rings the alarm: these clever machines aren't as clever as they look. First askClaude, then call in a human... read more  

Peer Programming with LLMs, For Senior+ Engineers
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@faun shared a link, 6 months, 2 weeks ago
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Want a humanoid, open source robot for just $3,000? Hugging Face is on it.

Hugging Facejust pulled the curtain back onHopeJR, a humanoid robot that swings 66 degrees of freedom—at just$3,000. This price tag shames the $16,000 slapped on Unitree's G1. Together with The Robot Studio, they've created this robot with a dash of Bender's charisma. The kicker? It's fully open-sou.. read more  

Want a humanoid, open source robot for just $3,000? Hugging Face is on it.
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@faun shared a link, 6 months, 2 weeks ago
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LLMOps: DevOps Strategies for Deploying Large Language Models in Production

LLMOpsshakes up the MLOps scene with tailor-made Kubernetes magic. It wrestlesGPU scheduling, caching, and autoscalingfor those behemothLLM deployments. Keep an eye out for serverless endpoints and model meshes—smooth scaling and a wallet-friendly operation... read more  

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@faun shared a link, 6 months, 2 weeks ago
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It’s not your imagination: AI is speeding up the pace of change

AI takes a victory lap:Mary Meeker revealsChatGPTsnagged 800 million users in a brisk 17 months. Meanwhile, the bean counters cheer as inference costs nosedived 99% in just two years. Profitability? That's still a cliffhanger... read more  

It’s not your imagination: AI is speeding up the pace of change
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@faun shared a link, 6 months, 2 weeks ago
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Perplexity offers training wheels for building AI agents

Perplexity Labsis your quick-draw tool for crafting apps and digital delights, powered by LLMs likeGPT-4 Omni. It’s a star where others stumble: fast, project-driven tasks. Expect example-heavy insights and real-world project demos. While competitors dawdle, it delivers. Need deep web browsing, code.. read more  

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@faun shared a link, 6 months, 2 weeks ago
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Why GCP Load Balancers Struggle with Stateful LLM Traffic — and How to Fix It

Deploying LLMs onGCP Load Balancersis like fitting a square peg in a round hole. These models aren't stateless, so skip HTTP, go straight forTCP Load Balancing. Toss in Redis to keep those sessions on a leash. Tweak load balancer settings to dodge mid-stream socket calamities. Embrace the power ofGK.. read more  

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@faun shared a link, 6 months, 2 weeks ago
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Using AI to outsmart AI-driven phishing scams

Phishing scamsare growing craftier, employing AI likeFraudGPTto weave through filters and masquerade as real emails, boosting scam rates by70%. AI can unveil sneaky phishing patterns humans miss, but it loves a good panic. It often cries wolf with false alarms and needs a babysitter to adjust to eve.. read more  

Using AI to outsmart AI-driven phishing scams
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@faun shared a link, 6 months, 2 weeks ago
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A visual introduction to vector embeddings

OpenAI's text-embedding-ada-002often gets a peculiar itch at dimension 196—vectors peaking awkwardly there. Entertext-embedding-3-small, swooping in to smooth out the distribution. Now, ontosimilarity metrics. For unit vectors, the dot product is your fast friend. It's interchangeable with cosine si.. read more  

A visual introduction to vector embeddings
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@faun shared a link, 6 months, 2 weeks ago
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We rewrote large parts of our API in Go using AI: we are now ready to handle one billion databases

Tursooverhauled its API withGoand AI, gunning for 1 billion databases. Think big, act smart. They squeezed every byte by adopting string interning. No more in-memory maps—they swapped them for aSQLite-backedLRU cache. The result? Leaner memory usage and hassle-free proxy bootstrapping... read more  

We rewrote large parts of our API in Go using AI: we are now ready to handle one billion databases