machine learning

Tips on how to Construct An AI Agent with Function Calling and GPT-5

and Large Language Models (LLMs) Large language models (LLMs) are advanced AI systems built on deep neural network akin to transformers and trained on vast amounts of text to generate human-like language. LLMs like ChatGPT,...

Google’s Gemini 3.0 Confirmed

Good morning. It’s Monday, October twentieth.On this present day in tech history: In 1971the Stanford "Hand–Eye" project quietly produced one in all the primary systems to integrate vision, reasoning, and robotic manipulation. Its...

Things I Learned by Participating in GenAI Hackathons Over the Past 6 Months

, but their frequency and accessibility have definitely grown quite a bit recently. Earlier, they were mostly reserved for predictive machine learning problems (think Kaggle), but now, the main focus, not less than for...

ChatGPT’s “golden hour” memory cull lands alongside Sora 2 upgrades

In partnership with Good morning. It’s Friday, October seventeenth.On today in tech history: In 2011Carnegie Mellon researchers released the RoboCup 3D simulation league AI. This league allowed autonomous agents to manage...

Stop Feeling Lost :  Methods to Master ML System Design

data scientist or ML engineer, learning machine learning system design is one of the crucial essential skills it is advisable know. It’s the bridge between constructing models and deploying solutions that drive actual...

Google Ships Real-Time AI in Meet

In partnership with Good morning. It’s Wednesday, October fifteenth.On this present day in tech history: In 1979a gaggle at MIT’s Architecture Machine Group logged a test of their “Put-That-There” multimodal interface...

Gemini 3 Leak?

Good morning. It’s Monday, October thirteenth.On this present day in tech history: In 2010Google announced its acquisition of BlindType, a tiny startup working on machine-learning–based text-entry prediction for touchscreens. The tech became a...

Methods to Perform Effective Agentic Context Engineering

has received serious attention with the rise of LLMs able to handling complex tasks. Initially, most discussions on this talk revolved around : Tuning a single prompt for optimized performance on a single...

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