ContentPosts from @kala..
Link
@kala shared a link, 5 hours ago
FAUN.dev()

Build AI Agents Worth Keeping: The Canvas Framework

MIT and McKinsey found a gap the size of the Grand Canyon: 80% of companies claim they’re using generative AI, but fewer than 1 in 10 use cases actually ship. Blame it on scattered data, fuzzy goals, and governance that's still MIA. A new stack is stepping in:product → agent → data → model. It flips..

Build AI Agents Worth Keeping: The Canvas Framework
Link
@kala shared a link, 5 hours ago
FAUN.dev()

Detect inappropriate images in S3 with AWS Rekognition + Terraform

A serverless AWS pipeline runs image moderation on autopilot - withS3,Lambda,Rekognition,SNS, andEventBridgeall wired up throughTerraform. When a photo gets flagged, it’s tagged, maybe quarantined, and triggers an email alert. Daily scan? Handled...

Detect inappropriate images in S3 with AWS Rekognition + Terraform
Link
@kala shared a link, 5 hours ago
FAUN.dev()

Grokipedia

Grokipedia just dropped - a Wikipedia remix built from LLM output, pitched as an escape from "woke" bias. The pitch? Bold. The execution? Rough. Entries run long. Facts bend. Citations wander. And the tone? Cold, context-free, and unmistakably machine-made. The usual LLM suspects are here: hallucina..

Link
@kala shared a link, 5 hours ago
FAUN.dev()

New trend: Programming by kicking off parallel AI agents

Senior engineers are starting to spin upparallel AI coding agents- think Claude Code, Cursor, and the like - to run tasks side by side. One agent sketches boilerplate. Another tackles tests. A third refactors old junk. All at once. Is it "multitasking on steroids"? Not just this as it messes with ho..

Link
@kala shared a link, 5 hours ago
FAUN.dev()

Why GPUs accelerate AI learning: The power of parallel math

Modern AI eats GPUs for breakfast - training, inference, all of it. Matrix ops? Parallel everything. Models like LLaMA don’t blink without a gang of H100s working overtime...

Why GPUs accelerate AI learning: The power of parallel math
Link
@kala shared a link, 5 hours ago
FAUN.dev()

Agentic AI and Security

Agentic LLM apps come with a glaring security flaw: they can't tell the difference between data and code. That blind spot opens the door to prompt injection and similar attacks. The fix? Treat them like they're radioactive. Run sensitive tasks in containers. Break up agent workflows so they never ju..

Agentic AI and Security
News FAUN.dev() Team
@kala shared an update, 6 hours ago
FAUN.dev()

AWS Unveils Project Rainier: Massive AI Cluster with Trainium2 Chips

Amazon Web Services

AWS has launched Project Rainier, a massive AI compute cluster with nearly half a million Trainium2 chips, in collaboration with Anthropic to advance AI infrastructure and model development.

AWS Unveils Project Rainier: Massive AI Cluster with Trainium2 Chips
 Activity
@kala added a new tool vLLM , 10 hours, 6 minutes ago.
News FAUN.dev() Team
@kala shared an update, 11 hours ago
FAUN.dev()

LangChain Secures $125M and Launches LangChain & LangGraph 1.0

LangChain

LangChain raised $125 million to enhance its agent engineering platform, introducing LangChain and LangGraph 1.0 with new tools like the Insights Agent and a no-code agent builder, aiming to transform LLM applications into reliable agents.

LangChain Secures $125M and Launches LangChain & LangGraph 1.0
 Activity
@kala added a new tool LangChain , 11 hours, 58 minutes ago.