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svpino/ml.school: Machine Learning School
svpino/ml.school: Machine Learning School
Machine Learning School. Contribute to svpino/ml.school development by creating an account on GitHub.
·github.com·
svpino/ml.school: Machine Learning School
Building Better AI Agents: The AI Enablement Stack
Building Better AI Agents: The AI Enablement Stack
Learn why the AI Enablement Stack is essential for modern AI development. 5 critical layers to build better, more capable intelligent agents.
·daytona.io·
Building Better AI Agents: The AI Enablement Stack
My 6 Secret Tips for Getting an ML Job in 2025
My 6 Secret Tips for Getting an ML Job in 2025
In this video, I share my 6 secret tips on how to get an ML job in 2025 because doing so feels almost impossible... At least, if you don't know what options ...
·youtube.com·
My 6 Secret Tips for Getting an ML Job in 2025
30 Year History of ChatGPT
30 Year History of ChatGPT
I follow the journey that led to the explosion of Large Language Models. From Jordan's pioneering work in 1986 to today's GPT-4, this documentary traces how ...
·youtube.com·
30 Year History of ChatGPT
Let's build GPT: from scratch, in code, spelled out.
Let's build GPT: from scratch, in code, spelled out.
We build a Generatively Pretrained Transformer (GPT), following the paper "Attention is All You Need" and OpenAI's GPT-2 / GPT-3. We talk about connections t...
·youtube.com·
Let's build GPT: from scratch, in code, spelled out.
PGVector's Missing Features — Trieve
PGVector's Missing Features — Trieve
PGVector offers infrastructure simplicity at the cost of missing some key features desireable in search solutions. We explain what those are in this blog.
·trieve.ai·
PGVector's Missing Features — Trieve
The rise of the AI crawler - Vercel
The rise of the AI crawler - Vercel
New research reveals how ChatGPT, Claude, and other AI crawlers process web content, including JavaScript rendering, assets, and other behavior and patterns—with recommendations for site owners, devs, and AI users.
·vercel.com·
The rise of the AI crawler - Vercel
Making it easier to build human-in-the-loop agents with interrupt
Making it easier to build human-in-the-loop agents with interrupt
While agents can be powerful, they are not perfect. This often makes it important to keep the human “in the loop” when building agents. For example, in our fireside chat we did with Michele Catasta (President of Replit) on their Replit Agent, he speaks several times about the human-in-the-loop component
·blog.langchain.dev·
Making it easier to build human-in-the-loop agents with interrupt
OpenAI Realtime API: The Missing Manual
OpenAI Realtime API: The Missing Manual
Everything we learned, and everything we think you need to know, from technical details on 24khz/G.711 audio, RTMP, HLS, WebRTC, to Interruption/VAD, to Cost, Latency, Tool Calls, and Context Mgmt
·latent.space·
OpenAI Realtime API: The Missing Manual
Reducing hallucinations in large language models with custom intervention using Amazon Bedrock Agents
Reducing hallucinations in large language models with custom intervention using Amazon Bedrock Agents
This post demonstrates how to use Amazon Bedrock Agents, Amazon Knowledge Bases, and the RAGAS evaluation metrics to build a custom hallucination detector and remediate it by using human-in-the-loop. The agentic workflow can be extended to custom use cases through different hallucination remediation techniques and offers the flexibility to detect and mitigate hallucinations using custom actions.
·aws.amazon.com·
Reducing hallucinations in large language models with custom intervention using Amazon Bedrock Agents
Supercharging LLM Application Development with LLM-Kit
Supercharging LLM Application Development with LLM-Kit
Discover how Grab's LLM-Kit enhances AI app development by addressing scalability, security, and integration challenges. This article discusses the challenges faced in LLM app building, the solution, the architecture of the LLM-Kit as well as the future plans of the LLM-Kit.
·engineering.grab.com·
Supercharging LLM Application Development with LLM-Kit
A guide to Amazon Bedrock Model Distillation (preview)
A guide to Amazon Bedrock Model Distillation (preview)
This post introduces the workflow of Amazon Bedrock Model Distillation. We first introduce the general concept of model distillation in Amazon Bedrock, and then focus on the important steps in model distillation, including setting up permissions, selecting the models, providing input dataset, commencing the model distillation jobs, and conducting evaluation and deployment of the student models after model distillation.
·aws.amazon.com·
A guide to Amazon Bedrock Model Distillation (preview)
AI SDK 4.0 - Vercel
AI SDK 4.0 - Vercel
Introducing PDF support, computer use, and an xAI Grok provider
·vercel.com·
AI SDK 4.0 - Vercel
AI Engineer Roadmap
AI Engineer Roadmap
Learn to become an AI Engineer using this roadmap. Community driven, articles, resources, guides, interview questions, quizzes for modern backend development.
·roadmap.sh·
AI Engineer Roadmap