Sitemap - 2023 - TheSequence
My Five Favorite AI Papers of 2023
Edge 355: A Taxonomy to Understand LLM Reasoning Methods
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 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
Edge 347: What is Constitutional AI?
Welcome to the World of Small(er) Language Models
Inside LlaVA: The Very Popular Open Source Alternative to GPT-4V
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*
📝 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
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
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
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
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
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 303: The Top Two Types Retrieval-Augmented Language Models
📝 Guest Post: Choosing the Right Vector Index For Your Project*
💡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 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]
📝 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*
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 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
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
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*
📌 EVENT: Join us at LLMs in Production conference – the first of its kind
🎙 ML platform podcast: Season 2 of MLOps Live from neptune.ai*
Edge 279: Cross-Silo Federating Learning
📝 Guest Post: An introduction to Similarity Search*
The Controversial AI Moratorium Letter
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
Edge 272: Inside Toolformer, Meta AI New Transformer Learned to Use Tools to Produce Better Answers
A Taxonomy to Understand Federated Learning
📝 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
Edge 267: A Summary of our Machine Learning Interpretability Series
💡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 257: Local Model-Agnostic Interpretability Methods
2023: The Year The Value Shifted from Infrastructure to Applications