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Lately I’ve been working with LLMs for the past few months across every part of the technology stack: from low-level (pytorch and ggml) to abstraction and orchestration layers (LangChain, Llama Index); from OpenAI to Claude to Llama and back; from prompt engineering to agent planning; from development to deployment, and now I’m working on monitoring and evaluation, pretraining.

I’ve also been talking with leaders across every part of the ecosystem: from the 10BedICU, OpenAI core team to futuristic indie projects at the AGI House to old-school businesses like Pratham Books who don’t even have a tech team that are desperate to use the technology.

One thing stands out across the landscape: LLMs are a new kind of product that have new kinds of user behavior, business expectations, and engineering requirements. I want to talk about a specific comment I hear a lot of people talk about, and how it creates a symphony of confusion and opportunity for designers, operators and engineers to build great products.


πŸ“• My Latest Projects:

  • LexiGenesis An repo to explain and understand how the evolution of LLM goes from pretraining -> finetuning -> benchmarking -> deployment -> application development over it

vignesh's Projects

2d-plotting icon 2d-plotting

A deep look into 2d graph plotting in Python using numpy and matplotlib

3d-graphs icon 3d-graphs

Building 3dimentional graps using matplotlib and mp_toolkits sublib to build a Z axes

baselines icon baselines

OpenAI Baselines: high-quality implementations of reinforcement learning algorithms

covid-19 icon covid-19

Coronaviruses are a group of related viruses that cause diseases in mammals and birds. In humans, coronaviruses cause respiratory tract infections that can be mild, such as some cases of the common cold, and others that can be lethal, such as SARS, MERS, and COVID-19. Symptoms in other species vary: in chickens, they cause an upper respiratory tract disease, while in cows and pigs they cause diarrhea. There are yet to be vaccines or antiviral drugs to prevent or treat human coronavirus infections.

ddpg-robotic-arm icon ddpg-robotic-arm

In this project, a double-jointed arm can move to target locations. A reward of +0.1 is provided for each step that the agent's hand is in the goal location. Thus, the goal of your agent is to maintain its position at the target location for as many time steps as possible.

dqn-unity-agent icon dqn-unity-agent

In this notebook, you will learn how to use the Unity ML-Agents environment to navigate the agent across the environment increasing its probabilty of hight rewards with constant exploration of new tasks

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