Sitemap - 2023 - TheSequence

My Five Favorite AI Papers of 2023

Inside Orca 2: Microsoft's Small Language Model that Outperforms Models 10x Larger in Reasoning Capabilities

Edge 355: A Taxonomy to Understand LLM Reasoning Methods

Apple GPT is Coming!

Inside Mixtral 8x7B: One of the Most Exciting Open Source LLM Ever Releases of this Year

Edge 353: A New Series About Reasoning in Foundation Models

Four Releases from Google DeepMind in a Single Week!

💡 Discover key GenAI trends from the annual ML Insider report

Edge 352: Inside the Embeddings Architecture Powering Job Recommendations at LinkedIn

The Sequence Chat: Hugging Face's Lewis Tunstall on ZEPHYR , RLHF and LLM Innovation

Edge 351: A Summary of Our Series About Fine-Tuning in Foundation Models

📝 Guest Post: Do We Still Need Vector Databases for RAG with OpenAI's Built-In Retrieval?

Gemini and Mistral MoE: Both Impactul Altough Very Different Releases

📝 Guest Post: How to Maximize LLM Performance*

Edge 350: Meet Zephyr: How Hugging Face's Instruction Fine Tuned LLM Outperformed Models 10 Times Its Size

Edge 349: Reinforcement Learning with AI Feedback

📹 [Webinar] Building a Real-Time Fraud Detection System at Signifyd

AWS’ Generative AI Strategy Starts to Take Shape and Looks a Lot Like Microsoft’s

📺 [Live Webinar] From Dream to Stream: Scaling ML Engineering at Flo Health

Inside Fuyu-8B: Adept's Super Innovative Multimodal Foundation Model for AI Agents

The Sequence Chat: Jeff Bussgang – Flybridge Capital, Harvard Business School, About Investing in Generative AI

Edge 347: What is Constitutional AI?

📝 Guest Post: Meet LoRAX: The Open Source System that Serves 1000s of Fine-Tuned LLMs on a Single GPU*

Welcome to the World of Small(er) Language Models

Inside LlaVA: The Very Popular Open Source Alternative to GPT-4V

The Sequence Chat: Doug Burger- Technical Fellow, Microsoft Research About Building Autonomous Agents, AutoGen and the Future of Generative AI

Edge 345: Deep Diving Into Reinforcement Learning with Human Feedback

📝 Guest Post: Creating your first Data Labeling Agent*

I Promise, this Editorial is NOT About OpenAI

😎 Private Preview: Build Real-Time AI Applications Using Only Python

Edge 344: LLMs and Memory is All You Need. Inside One of the Most Shocking Papers of the Year

Edge 343: Understanding Llama-Adapter Fine-Tuning

📝 Guest Post: Comparing Vector Databases, Vector Search Libraries, and Vector Search Plugins*

OpenAI is Starting to Look Like Apple in 2008

Edge 342: Who's Happy Potter? Inside One of the Most Fascinating Papers Published This Year

The Sequence Chat: Nathan Benaich, Air Street Capital About Investing in Generative AI

Edge 341: What is Prompt-Tuning?

📝 Guest Post: Introduction to DiskANN and the Vamana Algorithm*

DeepMind's AlphaFold-Latest is Pushing the Boundaries of Scientific Exploration

📣 ML Engineering Event: Join HelloFresh, Remitly, Riot Games, Uber & more at apply(ops)

Meet AutoGen: Microsoft's Super Innovative Framework for Autonomous Agents

Edge 339: What is Prefix-Tuning

📝 Guest Post: Adala – The First Open Source Data-Labeling Agent*

Generative AI is the New Wall Street Earnings Kingmaker, and Microsoft is the New Earnings King

📝 Guest Post: The Coming Wave of Specialized AI*

Edge 338: Inside WebAgent: Google DeepMind's Instruction-Tuned LLM that can Complete Tasks on Websites

Edge 337: Understanding QLoRA

📝 Guest Post: LLMs & humans: The perfect duo for data labeling

Fuyu-8B Makes the Case for Simple, Fast, and Powerful Generative AI Models

❗️🔎 Your expertise needed: weigh in on the ML Insider 2023 Survey

Inside OPRO: Google DeepMind’s New Method that Optimizes Prompts Better than Humans

The Sequence Chat: Shreya Rajpal, Co-Founder and CEO, Guardrails AI About Ensuring the Safety and Robustness of LLMs

Edge 335: LoRA Fine-Tuning and Low-Rank Adaptation Methods

📝 Guest Post: Retrieval Augmented Generation on Notion Docs via LangChain*

LLM Scaling Laws vs. Everything Else

📣 Event: Join Meta, PepsiCo, RiotGames, Uber & More at apply(ops)

Inside Microsoft's Four New AI Compilers for Accelerating Foundation Models

The Sequence Chat: Zhou Wangchunshu - CTO, AIWaves, on Generative AI Autonomous Agents

Edge 333: Understanding Parameter Efficient Fine Tuning

📡 WEBINAR: Unraveling prompt engineering

The Most Obvious Secret in AI: Every Tech Giant Will Build Its Own Chips

📣 Webinar: Learn how to fine-tune RAG and boost your content quality with Zilliz and 🔭 Galileo

Edge 332: Inside FlashAttention: The Method Powering LLM Scalability to Whole New Levels

The Sequence Pulse: Inside MLEnv, the Platform Powering Machine Learning at Pinterest

Edge 331: Universal Language Model Finetuning

A Week of Monster Generative AI Releases

📝 Guest Post: Build Trustworthy LLM Apps With Rapid Evaluation, Experimentation and Observability*

Edge 330: Inside DSPy: Stanford University's LangChain Alternative

Edge 329: Types of Fine-Tuning Methods in Foundation Models

Do Amazon and Apple Have Any Moats in Generative AI?

📣 Event: Announcing apply(ops), the Biggest Virtual Conference for the Global ML Community!

Edge 328: Inside AudioCraft: Meta AI’s New Family of Generative Audio Models

Edge 327: A New Series About Fine-Tuning Foundation Models

NVIDIA, The Most Influential VC In Generative AI

🎥 Building, Training & Deploying High-Quality ML Models—a Virtual Hands-On Lab

Meet SDXL 1.0: Stability AI New Text-to-Image Super Model

The Sequence Chat: Lianmin Zheng, UC Berkeley About Vicuna, Chatbot Arena and the Open Source LLM Revolution

Edge 325: A Summary of Our Series About New Techniques Foundation Models

Falcon-180B Takes Open Source LLMs Closer to GPT-4

🔥Building Plaid’s ML Fraud Detection Application—an apply() Fireside Chat

Edge 324: A Deep Dive Into Code Llama: Meta AI’s Open Source Entrance in the Code LLM Space

Edge 323: Types of Memory-Augmentation in Foundation Models

The Other OpenAI Competitor that Just Raised a Lot of Money

Edge 322: Inside Generative Agents : How Google and Stanford Researchers Used Generative AI to Learn to Simulate Human Behavior

Rico Mallozzi: Sapphire Ventures, About Investing $1B in Generative AI

Edge 321: Memory and Foundation Models

Meta's Coding Language Model Bet

Edge 320: Meet I-JEPA: Meta AI’s First Super Model Based on their Theory of Autonomous Intelligence

The Sequence Chat: Oren Etzioni – Allen AI, About Advancing Research in Foundation Models

Edge 319: The Factors Behind In-Context Learning

📺 Webinar: Create better features for your ML models

The NVIDIA GPU Scarcity Madness

📍 Hands-On Lab Next Week: Learn how to build great ML features and deploy them to production quickly and reliably

Inside LLM-AUGMENTER: Microsoft Research’s Reference Architecture to Extend LLMs with Memory, Knowledge, and External Feedback

The Sequence Pulse: How Uber Eats is Using Embeddings?

Edge 317: Understanding In-Context Learning

Keeping Up with NVIDIA's Generative AI Announcements

Inside CodeT5+: Salesforce's State-Of-The-Art Coding Language Model

The Sequence Pulse: A Deep Look Into How Yelp Uses Jupyter Notebooks at Scale

Edge 315: Tree-of-Thought Reasoning

CoreWeave, The GPU Champion That Isn't NVIDIA

💡Report: State of Applied ML 2023

Edge 314: A Deep Dive Into Llama 2: Meta AI LLM that has Become a Symbol in Open Source AI

The Sequence Chat: Gavin Uhma – CTO, Cape Privacy on Security Guardrails for LLMs

Edge 313: Multimodal Chain-of-Thought Reasoning

💡Whitepaper: Training Data for ML Models—A Deep Dive

More Foundation Models from Stability AI

📍 Webinar: Emerging architectures for LLM applications 🤖🧠🏗️

Textbooks are All You Need: How Microsoft's Phi-1 Outperformed Larger Code Language Models

Dr. Joseph Gonzalez, UC Berkeley: Creating Gorilla and Language Models that Can Call APIs

Understanding ReAct(Reason + Act) in LLMs

The Llama 2 Effect

How OpenAI Uses GPT-4 to Interpret the Functions of Neurons in Other Language Models

Luca Beurer-Kellner: ETH Zürich, Creator, Language Model Query Language,

Edge 309: What is Active Prompting?

Some Key Facts About Anthropic’s Claude 2 Release

Meet LMQL: An Open Source Query Language for LLMs

The Sequence Chat: Emmanuel Turlay – CEO, Sematic

Edge 307: Learning About Program-Aided Language Models

“The Other” Enterprise Generative AI Platforms

💡Webinar: Designing & Scaling FanDuel's Machine Learning Platform

Meet Open Assistant: The Open Source Platform for Light, High-Performance LLMs

The Sequence Pulse: The Architecture Powering Data Drift Detection at Uber

Edge 305: In-Context Retrieval-Augmented Language Models

💡Webinar: To train or not to train your 🅻🅻🅼

Open Source Scored the First Major M&A of the Generative AI Era

Edge 304: Inside AlphaDev: DeepMind’s Newest Breakthrough Model that Was Able to Discover New Computer Science Algorithms

The Sequence Chat: Daniel J. Mankowitz, DeepMind on Building AlphaDev to Discover New Computer Science Algorithms

Edge 303: The Top Two Types Retrieval-Augmented Language Models

📝 Guest Post: Choosing the Right Vector Index For Your Project*

The Generative Audio Momentum

💡Webinar: Designing & Scaling FanDuel's ML Platform—Best Practices & Lessons Learned

Edge 302: Inside MPT-7B: MosaicML's Suite of Open Source LLMs that Supports 65k Tokens

The Sequence Chat: Vipul Ved Prakash, CEO, Together on Decentralized, Open Source Foundation Models

Edge 301: Retrieval-Augmented Language Models Methods

📝 Guest Post: Achieving real enterprise outcomes with GPT-You, not GPT-X*

Yann LeCun's Vision Starts Materializing

📝 Guest Post: Democratizing Vector Databases: Empowering Access & Equality*

Edge 300: Meet Falcon LLM: The Most Powerful Open Source LLM Released to Date

The Sequence Pulse: Inside Merlin, the Platform Powering Machine Learning at Shopify

Edge 299: A Taxonomy to Understand Tool-Augmented Language Models

📝 Guest Post: Enhancing ChatGPT's Efficiency – The Power of LangChain and Milvus*

The AlphaDev Milestone: A New Model that is Able to Discover and Improve Algorithms

Meet the LLM Garden 🪴🌱

Meet MiniGPT-4: The Open Source Vision-Language Model that Matches the Performance of GPT-4

The Sequence Chat: Raza Habib, Humanloop on Building LLM-Driven Applications

Edge 297: Tool-Augmented Language Models

📺 See how programmatic labeling is the key to using LLMs [Live Demo]

The Next RLHF Effect: Three Breakhroughts that can Unlock the Next Wave of Innovation in Foundation Models

This week on TuringPost

📝 Guest Post: Stop Hallucinations From Hurting your LLM Powered Apps*

Edge 296: Inside OpenAI's Method to Use GPT-4 to Explain Neuron's Behaviors in GPT-2

The Sequence Chat: Rohan Taori on Stanford's Alpaca, Alpaca Farm and the Future of LLMs

Edge 295: Self-Instruct Models

📝 Guest Post: How to build a responsible code LLM with crowdsourcing*


Announcing Turing Post

📢 Event: ML practitioners from Affirm, Block, Remitly, Tide & more share their learnings from building risk & fraud detection systems

Edge 294: Inside StarCoder: Hugging Face's New LLM that Can Generate Code in Over 80 Programming Languages

The Sequence Chat: Hugging Face's Leandro von Werra on StarCoder and Code Generating LLMs

Edge 293: Instruction Following Language Models

📝 Guest Post: How to Customize Auto-GPT for Your Unique Use Case: A Comprehensive Guide*

The Undisputed Champion of Open Source Generative AI

📍 Join 1000s of data scientists from around the globe at The Future of Data-Centric AI on June 7-8

Meet OpenChatKit: The Open Source Alternative to ChatGPT

The Sequence Chat: Sharon Zhou: CEO, Lamini on RLHF and Fine-Tuning LLMs

Edge 291: Reinforcement Learning with Human Feedback

Google’s Somewhat “Moat-less “ AI Week

💥 Win a Lambda GPU workstation with your AI paper submission!

Edge 290: Inside Koala, Berkeley University’s LLaMA-Based Model Fine-Tuned with ChatGPT Dialogues

The Sequence Chat: Deyao Zhu and Ju Chen on MiniGPT-4

Edge 289: What is Chain of Thought Prompting?

The Hemingway Effect and Generative AI Coding Revolution

📌 Event: The Future of Data-Centric AI 2023

Edge 288: Inside DeepSpeed-Chat: Microsoft’s New Framework to Create ChatGPT-Like Models Based on Human Feedback

Edge 287: A New Series About New Techniques in Foundation Models

The Generative AI Cyber Security Week

📌 Meet Elemeta: Metafeature Extraction for Unstructured Data*

Edge 286: Vicuna, the LLaMA-Based Model that Matches ChatGPT Performance

The Sequence Chat: Microsoft's Evan Chaki on Semantic Kernel and Combining LLMs with Conventional Programming Languages

Edge 285: A Recap Of Our Series About Federated Learning

📝 Guest post: Elemeta: Metafeature extraction for unstructured data*

Open Source Generative AI is Experiencing a "Linux Moment" but it Needs an "Apache Moment"

💡The Buyer’s Guide to Evaluating ML Feature Stores & Feature Platforms

Edge 284: Meet Dolly 2.0: One of the First Open Source Instruction Following LLMs

The Sequence Chat: Consensys's Lex Sokolin on Generative Art and Philosophical Principles of Generative AI

Edge 283: Federated Learning and Differential Privacy

📝 Guest Post: How to Enhance the Usefulness of Large Language Models*

Big vs. Small, Open Source vs. API Based, the Philosophical Frictions of Foundation Models

📌 Webinar: Improving search relevance with ML monitoring

Inside LangChain: The Super Popular LLM Framework You Need to Know About

The Sequence Chat: Salesforce Research's Junnan Li on Multimodal Generative AI

Edge 281: Cross-Device Federated Learning

📝 Guest Post: Caching LLM Queries for Improved Performance and Cost Savings*

The LLama Effect: How an Accidental Leak Sparked a Series of Impressive Open Source Alternatives to ChatGPT

📌 EVENT: Join us at LLMs in Production conference – the first of its kind

📝 Guest Post: Using LLMs from Hugging Face? Fix your model failure points 10x faster with Galileo Data Intelligence*

Inside Alpaca: The Language Model from Stanford University that can Follow Instructions and Match GPT-3.5

🎙 ML platform podcast: Season 2 of MLOps Live from*

Edge 279: Cross-Silo Federating Learning

📝 Guest Post: An introduction to Similarity Search*

The Controversial AI Moratorium Letter

📝 Guest Post: Switching from Spreadsheets to Experiment Tracker and How It Improved My Model Development Process*

Edge 278: Inside LaMDA, Google's Alternative to GPT-4

📌 Learn the ABCs of LLMs from OpenAI, 🦙 LlamaIndex, Hugging Face 🤗, and Others At Arize:Observe

Edge 277: Federated Transfer Learning

OpenAI’s Frantic Pace of Releases and the Generative AI Short Innovation Cycles

📝 Guest Post: Guide to Building an ML Platform*

LLaMA is Meta AI's New LLM that Matchest GPT-3.5 Across Many Tasks Despite Being Quite Smaller

Edge 275: Understanding Vertical Federated Learning

Results of the Survey: 📝 How is MLOps more than just tools?

Another Monster Generative AI Week

📌 Webinar: See How Tecton Enables Data Teams to Shift Notebook Development Into Production

Sparrow Might be the Foundation of DeepMind's ChatGPT Competitor

S. Somasegar on the Present and Future of Generative AI

Edge 273: Horizontal Federated Learning

What a Week for Generative AI

Edge 272: Inside Toolformer, Meta AI New Transformer Learned to Use Tools to Produce Better Answers

A Taxonomy to Understand Federated Learning

ChatGPT and Whisper APIs

📝 How is MLOps more than just tools?

Inside Claude: The ChatGPT Competitor that Just Raised Over $1 Billion

Edge 269: A New Series About Federated Learning

Meta and Amazon Generative AI Moves

📝 Guest Post: Harder than Expected: Why Large Enterprises Are Challenged by AI/ML*

Inside BLOOM: How Thousands of AI Researchers Created an Open Source ChatGPT Alternative

💡TOMORROW: Chip Huyen & Kevin Stumpf on Making the Jump to Real-Time ML

Who Has The Vision?

😐 A Snag on the Edge

Edge 267: A Summary of our Machine Learning Interpretability Series

The ChatGPT Challengers

💡Share Your Thoughts on Applied ML for a $25 Amazon Gift Card*

Edge 266: The Magic Behind ChatGPT: Reinforcement Learning with Human Feedback

📍 Free Guide: Maximize the ROI of your AI/ML Investment: Building vs. Buying Monitoring Solutions*

Edge 265: Interpretability Methods for Deep Neural Networks

Has OpenAI Hit Escape Velocity?

Edge 264: Inside Muse: Google’s New Text-to-Image Super Model

Edge 263: Local Model-Agnostic Interpretability Methods: Counterfactual Explanations

The Most Exciting Alliance in AI

Edge 262: NVIDIA’s Get3D is a Generative AI Model for 3D Shapes

Edge 261: Local Model-Agnostic Interpretability Methods: LIME

New Generative AI Innovations from Google and Salesforce

📝 Guest Post: Winning the AI Game as a Medium-Sized Business*

Edge 260: Data2vec 2.0 is Meta AI's New Self-Supervised Learning Model for Vision, Speech and Text

📌 Event: Robust & Responsible AI Summit with Andrew Ng & industry leaders

Edge 259: Local Model-Agnostic Interpretability Methods: SHAP

NVIDIA Latest Push in Generative AI the Metaverse

Edge 258: Inside OpenAI's Point-E: The New Foundation Model Able to Generate 3D Representations from Language

Edge 257: Local Model-Agnostic Interpretability Methods

2023: The Year The Value Shifted from Infrastructure to Applications