June 2023

What Is AI Security?

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In one of the recent interviews, Elon Musk has warned humanity that artificial intelligence could lead to “civilization destruction”. While talking about AI, so advanced that it will threaten our society, to most experts seems preliminary, one thing is certain: we depend on artificial intelligence as much as AI depends on us. Artificial intelligence systems run in your phone to help you capture better pictures, find relevant materials online, and optimize your storage space. But it all comes […]

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LLM Powered Autonomous Agents

LLM Powered Autonomous Agents

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Building agents with LLM (large language model) as its core controller is a cool concept. Several proof-of-concepts demos, such as AutoGPT, GPT-Engineer and BabyAGI, serve as inspiring examples. The potentiality of LLM extends beyond generating well-written copies, stories, essays and programs; it can be framed as a powerful general problem solver. Agent System Overview In a LLM-powered autonomous agent system, LLM functions as the agent’s brain, complemented by several key components: Planning Subgoal and decomposition: The agent breaks […]

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Bringing Fun into FP: Interview with Impure Pics

Bringing Fun into FP: Interview with Impure Pics

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In this article, we interview Jay, the mastermind behind Impure Pics. If you have been on Haskell Twitter for a while, you’ve definitely seen some of his drawings. In addition to that, he’s recently started a YouTube channel where he distills functional programming concepts in a fun and accessible manner. We have had the great opportunity to collaborate with Jay a number of times, the latest being a special edition tee celebrating one of the things that makes […]

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We're Writing a Book! "Hands-On Large Language Models"

We’re Writing a Book! “Hands-On Large Language Models”

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I’m super excited to co-write “Hands-On Large Language Models” with Maarten Grootendorst and published by O’Reilly Media! We aim to distill the main intuitions for using language models for text understanding and generation with LOTs of visuals. Thanks for reading Language Models and Machine Learning! Subscribe for free to receive new posts and support my work. We’ll be posting updates about the writing process on social media and on this newsletter. I’d love to hear your thoughts and […]

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Finetuning Falcon LLMs More Efficiently With LoRA and Adapters

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Finetuning allows us to adapt pretrained LLMs in a cost-efficient manner. But which method should we use? This article compares different parameter-efficient finetuning methods for the latest top-performing open-source LLM, Falcon. Using parameter-efficient finetuning methods outlined in this article, it’s possible to finetune an LLM in 1 hour on a single GPU instead of a day on 6 GPUs.

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What is Quantum Computing?

What is Quantum Computing?

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Is quantum computing a reality or mere science fiction? Do quantum computers already exist or are they still in the realm of speculation? Will quantum computers substitute general-purpose computers? How far are we from witnessing their commercial production, if it ever happens? In this blog post, we explore facts, myths, and concerns surrounding the advent of a new technological revolution. What is quantum computing? Quantum computing is a field in computer science that draws upon the principles of […]

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We may finally crack Maths. But should we?

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Automating mathematical theorem proving has been a long standing goal of artificial intelligence and indeed computer science. It’s one of the areas I became very interested in recently. This is because I feel we may have the ingredients needed to make very, very significant progress: a structured search space with clear-cut success criterion that can be algorithmically generated: the language of formal mathematics a path to obtaining very good heuristics to guide search in the space – LLMs […]

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Introduction to Tiny ML

Introduction to Tiny ML

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TinyML – machine learning in embedded devices – is actively gaining popularity. According to ABI Research’s latest whitepaper, TinyML device shipments will grow to 2.5 Billion in 2030, up from 15 million in 2020. With the vast proliferation of intelligent devices, it has become vital to equip them with machine-learning capabilities that run smoothly and fast, even in limited memory and computational power conditions. This post will explain how TinyML works and why it is important. TinyML Vs. […]

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