Summary: Part I of Sutton and Barto's book covers fundamental Reinforcement Learning techniques, while Part II focuses on using deep neural networks for approximate solutions. The upcoming series will benchmark algorithms in Gridworld environments to identify the most effective methods.
Amazon Bedrock Evaluations introduces LLM-as-a-judge technique for evaluating models and RAG systems, enabling custom metrics for tailored assessments. Organizations can now systematically evaluate models and applications with automated, human-like quality at scale, using built-in or custom metrics.
OpenAI backtracks on for-profit transformation, nonprofit arm to control ChatGPT. Decision made after input from civic leaders and attorneys general.
Amazon faces ethical responsibility to prevent chatbot-written books on sensitive topics like managing ADHD. AI-generated works flood marketplace with misleading information, from travel guides to mushroom foraging books.
AI labs are preparing for rogue AIs colluding against humans, but the real threat is AI making humans obsolete in all aspects of life. AI could replace humans economically, culturally, and socially, leaving us wondering our place in a world where AI does everything better.
Tech billionaires like Musk and Bezos have always had a far-right libertarian core, not a sudden shift in ideology. Silicon Valley's venture capitalists and CEOs have long embraced a quasi-religious belief in tech salvation, despite outward political affiliations.
L¹ and L² norms play different roles in AI models, affecting accuracy and generalizability. Understanding their distinctions is crucial in tasks like GAN image generation.
The future of Data Science lies in Generative AI development. AI Agents can now do more than chat, like scheduling appointments and searching the internet.
QARC & AWS team created WordFinder to help individuals with aphasia communicate using generative AI. Hack For Purpose event tackled challenges faced by social good organizations in Australia.
Knowledge Graphs connect concepts, entities, and relationships to enhance LLM performance in information retrieval. GraphRAG uses graph-based knowledge representation to improve LLM reasoning beyond traditional vector approaches, enabling inter-document level reasoning for more effective information retrieval.
MIT researchers developed LinOSS, a stable AI model inspired by neural oscillations, outperforming existing models in long sequence analysis. LinOSS offers efficient predictions for various fields, from health-care analytics to financial forecasting, bridging biological inspiration with computational innovation.
DeepType utilizes neural networks for clustering, extracting meaningful structure from data for more insightful analysis and predictions. By training on task-relevant representations, DeepType enhances clustering accuracy and reveals valuable insights, as seen in patient groupings based on genetic data for improved survival rate correlations.
A SaaS saved 79% on cloud bill and reduced latency from 1.9s to 140ms in 48 hours by optimizing queries and documents. They fixed N + 1 waterfalls, tamed unbounded cursors, and split jumbo docs, slashing costs from $15,284 to $3,210/mo.
AI agents promise to automate tasks, but human review remains essential due to error rates. Implementing AI Decision Circuits with redundancy can enhance accuracy in agentic processes.
Kernel ridge regression (KRR) uses a kernel function to predict values and prevent overfitting. Implementing KRR in JavaScript is a challenging yet rewarding puzzle, offering accurate predictions and various training techniques like stochastic gradient descent.