(오늘의 짤방: Untitled089_v1_Backup.ipynb via @paulabartabajo_)
- 빅데이터/인공지능
- WhatsApp-Llama - 자신의 왓츠앱 대화로 LLM 파인튜닝 하기 (github.com/Ads-cmu)
- Quantifying GPT-4’s Hidden Regressions Over Time
- LLM Output Parsing: Function Calling vs. LangChain
- Now You See Me (CME): Concept-based Model Extraction
- Why transformative artificial intelligence is really, really hard to achieve
- EfficientML.ai Lecture 5 - Quantization (Part I) (MIT 6.5940, Fall 2023)
- But with this prompt, you can get GPT-4 to emulate any writing style you want.
- Learn ML in 3 steps
- Object Detection Models 🥥 (Hugging Face)
- OpenAI Cookbook - Open-source examples and guides
- A test of artificial intelligence
- GN⁺: Microsoft, 신개념 단백질 생성 AI EvoDiff를 오픈소스로 공개 (techcrunch.com)
- You can now extract a full Pydantic object from any doc with 1 LLM call.
- The beauty of using LLMs to evaluate e2e LLM/RAG is that they can not only be used as a “human judge” to compare generated vs. ground-truth response 🧑⚖️, but also be used to generate the “ground-truth” eval dataset in the first place 🧬
- FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness
- Distilling step-by-step: Outperforming larger language models with less training data and smaller model sizes
- 드롭박스, 델타, PwC 등 안쓰는 곳이 없다··· 현재 기업에서 AI를 활용하는 방식 12가지
- 오라클 래리 엘리슨 “생성형 AI, 기존 AI와는 달라··· 역사상 가장 중요한 기술”
- LLM 모델 기반 서비스 실전 가이드
- 구글 딥마인드 “AI에 심호흡 지시하면 수학 능력 향상"
- What makes LLM tokenizers different from each other? GPT4 vs. FlanT5 Vs. Starcoder Vs. BERT and more
- GN⁺: Cisco, Splunk 인수 (splunk.com)
- 가족들에게 꼭 알려주세요! 구글 렌즈와 바드가 결합한 버전 한국어 출시!
- Announcing Microsoft Copilot, your everyday AI companion
- Distance Metrics in Vector Search
- "우린 벌써 뛰고 있어" 생성형 AI를 워크플로우와 결합한 기업 3곳의 경험
- “그래도 코딩하는 임원은 거의 없다” 로우코드ㆍ노코드 개발 ‘이상과 현실’
- “사람처럼 대화하고 상호작용한다” 아마존, 생성형 AI 탑재한 ‘알렉사’ 공개
- “객체 추적부터 트랙 분할까지” 알아두면 쓸모 있고 유용한 무료 ‘AI 도구’ 9선
- The Upcoming AI Wars and The Science Behind Multimodal Large Language Models (MLLMs)
- “Here’s one cool trick to avoid lost in the middle problems in your RAG pipeline” ‼️👇
- LLMs & Knowledge Graphs
- A partnership with Howard University to improve speech technology for Black voices
- Extracting actionable data from structured documents with Amazon Textract, AWS Lambda and Amazon S3
- Topics per Class Using BERTopic - How to understand the differences in texts by categories
- Introducing Code Llama, a state-of-the-art large language model for coding
- 아마존, 상품 목록 작성 돕는 새 생성형 AI 도구 배포
- '작을 수록 좋은 것' 대규모 언어 모델은 축소되어야 한다
- 영국 CMA, ‘건강한’ AI 파운데이션 모델 위한 7원칙 제시
- “범용 AI는 기업용으로 부족”··· B2B 글쓰기 전문 LLM 만든 라이터, 1억 달러 투자 유치
- PyTorch Model Performance Analysis and Optimization — Part 6
- ‘흥분도 비관도 모두 옳다’ 생성형 AI의 경계선 체득하기
- “더 똑똑하고 유용해졌다” 구글, 지메일·유튜브·구글 문서 등에 바드 통합
- All You Need to Know about Vector Databases and How to Use Them to Augment Your LLM Apps
- Doctor Dignity is a Large Language Model that can pass the US Medical Licensing Exam.
- 메타가 개발한 대규모 언어 모델, ‘라마 2’란 무엇인가?
- 네이버, 생성형 AI 검색 ‘큐’(Cue:) 베타 서비스 시작
- 자율주행 레벨 3 언제 메인스트림 될까?
- About GitHub Copilot Chat
- Migrating From Unity to Other Game Engines
- Create Cinematic AI Videos with Pika Labs
- Language models are powerful, but they have limitations. Integrating LLMs with specialized tools, which is one of the most promising directions of AI research, can make them 10X more effective. Here are the four different styles of tools being explored…
- Bard can now connect to your Google apps and services
- DSPy: Programming—not prompting—Foundation Models
- Binary Quantization - Vector Search, 40x Faster
- GN⁺: DALL·E 3 (openai.com)
- Building RAG from Scratch (Lower-Level)
- DeepEval provides a Pythonic way to run offline evaluations on your LLM pipelines so you can launch comfortably into production.
- The Rise and Potential of Large Language Model Based Agents: A Survey
- How Are Consumers Using Generative AI?
- “파리 항공편 찾아줘”…구글 바드, 이젠 똘똘한 AI 비서
- Optimizing LLMs from a Dataset Perspective
- Optimizing your LLM in production
- 10 Ways to Improve the Performance of Retrieval Augmented Generation Systems
- Summarization is (Almost) Dead
- Generative AI Lifecycle Patterns
- Here are 4 RAG techniques implemented in @llama_index 🦙
- 문과생 AI수업 확대…박사학위 속성 취득
- 구글 Bard, Extention 기능을 통한 새로운 사용법 제안 (blog.google)
- Consciousness in Artificial Intelligence: Insights from the Science of Consciousness
- 올거나이즈, 금융특화 AI 언어모델 '알리 파이낸스 LLM' 출시
- RAG is more than just embedding search
- Multimodal Foundation Models: From Specialists to General-Purpose Assistants
- Language Modeling Is Compression
- This notebook demonstrates how to download Microsoft and Google Building Footprints and merge them into a single vector file.
- leafmap - A Python package for geospatial analysis and interactive mapping in a Jupyter environment.
- NExT-GPT: Any-to-Any Multimodal LLM
- Where do we most need AI in healthcare?
- Google's next big swing at AI rumored to launch this fall
- SceneXplain's Image-to-JSON: Extract Structured Data from Images with Precision
- petals - Run large language models at home, BitTorrent-style. Fine-tuning and inference up to 10x faster than offloading
- PDFTriage: Question Answering over Long, Structured Documents
- Candle is a minimalist ML framework for Rust with a focus on performance (including GPU support) and ease of use.
- Build and Scale a Powerful Query Engine with LlamaIndex and Ray
- HumanEval: Hand-Written Evaluation Set
- Augmenting LLMs: Fine-Tuning or RAG?
- Why not let developers use ChatGPT during an interview?
- Serving ML Models in Production: Common Patterns
- Mlxtend (machine learning extensions) is a Python library of useful tools for the day-to-day data science tasks.
- Feature-engine - A Python library for Feature Engineering and Selection
- GN⁺: 애플의 새로운 'Transformer' 기반 예측 텍스트 모델 (jackcook.com)
- The AutoML Dilemma - An Infrastructure Engineer’s Perspective
- MediaPipe FaceStylizer: On-device real-time few-shot face stylization
- 48시간만에 국내 여행 업계 최초 AI서비스 만든 사연
- NanoSAM is a Segment Anything (SAM) model variant that is capable of running in 🔥 real-time 🔥 on NVIDIA Jetson Orin Platforms with NVIDIA TensorRT.
- Towards a new SymPy: part 1 - Outline¶
- Awesome Machine Learning On Source Code
- Machine Learning for Big Code and Naturalness
- llama2를 파인 튜닝 하고 있는 사람들 (news.ycombinator.com)
- 알아두면 만사가 편해지는 머신러닝 10가지 알고리즘
- Centaurs and Cyborgs on the Jagged Frontier - I think we have an answer on whether AIs will reshape work....
- LLM Guard - The Security Toolkit for LLM Interactions
- Candle is a minimalist ML framework for Rust with a focus on performance (including GPU support) and ease of use.
- Candle Segment Anything - Rust/WASM Demo
- Fine-Tuning Llama-2: A Comprehensive Case Study for Tailoring Models to Unique Applications
- Programmatic Custom Model Creation by cohere
- Deploy Generative AI Models on Amazon EKS
- The Belebele Benchmark for Massively Multilingual NLU Evaluation
- PyGraft: Configurable Generation of Schemas and Knowledge Graphs at Your Fingertips
- Biomedical Vision-Language Models (VLMs)
- LLM now provides tools for working with embeddings
- Renumics Spotlight - Interactively explore unstructured datasets from your dataframe.
- AudioSR: Versatile Audio Super-resolution at Scale
- '통화녹음' 안 되는 아이폰···SKT AI로 가능해진다
- [seq2seq] 간단한 seq2seq 모델 구현
- Radiology-Llama2: Best-in-Class Large Language Model for Radiology
- How to Optimize FastAPI for ML Model Serving
- 벡터 유사도 검색이 무엇인가요? (What is Vector Similarity Search?) (discuss.pytorch.kr)
- 머신러닝 분야의 임베딩에 대한 상세한 가이드 (The Full Guide to Embeddings in Machine Learning)
- ⓍTTS is a super cool Text-to-Speech model that lets you clone voices in different languages by using just a quick 3-second audio clip.
- ProPainter: Improving Propagation and Transformer for Video Inpainting
- 생성형 AI의 어두운 진실 7가지
- “윈도우 사진 앱의 르네상스” 마이크로소프트, 새로운 AI 기능 테스트
- “나랑 스무고개 할래?” 클로바X·바드·빙챗에 물으니…
- Generative Image Dynamics
- How Large Language Models Assisted a Website Makeover
- Choral Explanations
- 7 Frameworks for Serving LLMs
- Photoguard - Interactive Demo: Raising the Cost of Malicious AI-Powered Image Editing
- Zoom updates terms of service to clarify that it won’t use your calls to train AI
- Why watermarking AI-generated content won’t guarantee trust online
- Cryptography may offer a solution to the massive AI-labeling problem
- RT-2: New model translates vision and language into action
- Maccarone: AI-managed code blocks in Python ⏪⏩
- Lecture Notes for 8.370/18.435 Quantum Computation from Fall 2022(MIT)
- Who Answers It Better? An In-Depth Analysis of ChatGPT and Stack Overflow Answers to Software Engineering Questions
- US judge: Art created solely by artificial intelligence cannot be copyrighted
- textfx - AI-powered tools for rappers, writers and wordsmiths.
- Introducing txtai, the all-in-one embeddings database
Add Natural Language Understanding to any application
- Best Practices for LLM Evaluation of RAG Applications - A Case Study on the Databricks Documentation Bot
- AI, ML, Data Engineering News Roundup: Jupyter AI, AudioCraft, OverflowAI, StableCode and Tabnine
- Bots are better than humans at cracking ‘Are you a robot?’ Captcha tests, study finds
- LINGO-1: Exploring Natural Language for Autonomous Driving
- GN⁺: ExLlamaV2: 일반 GPU에서 로컬 LLMs를 실행하기 위한 빠른 추론 라이브러리 (github.com/turboderp)
- 오픈AI의 챗GPT 엔터프라이즈, 마이크로소프트와는 어떤 관계?
- 영화 음악부터 소음까지 생성··· 스테이빌리티AI, AI 음악 생성 모델 ‘스테이블 오디오’ 공개
- Dive in with Coral - Coral is a knowledge assistant for enterprises
to supercharge the productivity of their most strategic teams.
- Stock Market Prediction on High-Frequency Data Using Generative Adversarial Nets
- How to keep your ML spending under control
- How will LLMs disrupt different data engineering tasks?
- NLP research over the years:
- Run LLMs on Any GPU: GPT4All Universal GPU Support
- supervision - We write your reusable computer vision tools. Whether you need to load your dataset from your hard drive, draw detections on an image or video, or count how many detections are in a zone.
- 애플은 지금 시리2.0을 향해 가고 있을까?
- “LLM 개발을 더 간편하게” 랭체인(LangChain)의 이해
- Fine-Tuning Your Embedding Model to Maximize Relevance Retrieval in RAG Pipeline
- ‘AI 저작권 문제 대신 배상’… MS, 코파일럿 저작권 약정 도입
- “시멘틱 데이터로 프롬프트 엔지니어링 패러다임 전환” 키토크AI 도준웅 대표
- "AI가 굴리는데 영 신통찮네"…적자 쌓이는 로보어드바이저社 [긱스]
- GN⁺: Stable Audio - 빠른 타이밍 조절형 Latent Audio Diffusion (stability.ai)
- 🤖 New on #KaggleModels! Introducing Llama 2 from @MetaAI: a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 70 billion parameters. 📚 Explore, share, and upvote your favorite notebooks. Happy Kaggling!
- ArXiv QA: (TBD) Automated ArXiv question answering via large language models
- This is a very initial release of ExLlamaV2, an inference library for running local LLMs on modern consumer GPUs.
- A Principal Odor Map Unifies Diverse Tasks in Human Olfactory Perception
- Face Recognition Based Attendance System Using Python
- LLM Applications: A comprehensive guide to building RAG-based LLM applications for production.
- Finetuning an Adapter on Top of any Black-Box Embedding Model
- Stable Audio - Create music with AI.
- How to deploy ML models painlessly
- Generative AI exists because of the transformer (Interactive article)
- LLMs journey from Word2Vec to ChatGPT in a single frame 🤯
- NVIDIA, LLM 추론을 가속하는 TensorRT-LLM 오픈소스 공개 (developer.nvidia.com)
- Discover LlamaIndex: Bottoms-Up Development with LLMs (Part 5, Retrievers + Node Postprocessors)
- Can LLMs Really Reason and Plan?
- Morgan Stanley launches OpenAI chatbot for investment advice
- 자바도 머신러닝 시대 준비··· GPU, 외부 모델 지원하는 ‘바빌론 프로젝트’ 시작
- GPT-4 앞지른 ‘무료 AI’…수조 쓴 빅테크 고민 깊어진다
- Machine Learning’s Public Perception Problem
- Nvidia의 AI 성공 비밀 (spectrum.ieee.org)
- I made a transformer by hand (no training!)
- imgbeddings - A Python package to generate embedding vectors from images, using OpenAI's robust CLIP model via Hugging Face transformers.
- CLIP (Contrastive Language-Image Pre-Training) is a neural network trained on a variety of (image, text) pairs.
- GPT and BERT: A Comparison of Transformer Architectures
- DiffBIR: Towards Blind Image Restoration with Generative Diffusion Prior
- DiffBIR colab notebook
- High Quality Entity Segmentation
- 🐍 Natural Language Processing With Python's NLTK Package 📰
- Financial series prediction using Attention LSTM
- Asking 60+ LLMs a set of 20 questions
- 세계 최대 규모 암 진단 AI 개발 뛰어든 마이크로소프트
- From Sparse to Dense: GPT-4 Summarization with Chain of Density Prompting
- Prompt Engineering: A Practical Example
- The Project Gutenberg Open Audiobook Collection - Thousands of free and open audiobooks powered by Project Gutenberg, Microsoft, and MIT
- Hybrid Search Explained
- We’ve built hybrid search for Postgres/pgvector (thanks to
@thesourabhd and @disiok for leading) - this is exciting! 🔥
- Are self-driving cars already safer than human drivers?
- GPT in 60 Lines of NumPy
- GN⁺: 20개의 질문으로 60개의 LLM에게 묻다 (benchmarks.llmonitor.com)
- DeepMIR - Teaching material for the course (CommE5070) "Deep Learning for Music Analysis and Generation" I taught at National Taiwan University (2023 Fall).
- 속도와 파이썬, 두 마리 토끼 잡기: 딥러닝 시 빠른 파이썬 코드 실행을 위한 CUDA 그래프 사용법 (discuss.pytorch.kr)
- A list explaining key ML concepts and papers
- 흉부 엑스레이 추적 검사, 인공지능이 판독 효율성 높였다...진단 정확도 80%
- 챗GPT 연계 이후 돈 잘 버는 AI 서비스 3곳
- Researchers use machine learning to predict drug approval chances before clinical trials
- GN⁺: TSMC, AI 칩 부족이 18개월 더 지속될 것이라 경고 (theregister.com)
- GPT Can Solve Mathematical Problems Without a Calculator
- 4 Skills the Next Generation of Data Scientists Needs to Develop
- GN⁺: EmojiGen - AI를 활용한 Emoji 생성기 오픈소스 (emoji.fly.dev)
- Introduction to Anomaly Detection in Python with PyCaret
- Rivet, the IDE for creating complex AI agents and prompt chaining, and embedding it in your application.
- Scaling the Instagram Explore recommendations system
- 하드웨어
- 읽을거리
EOB
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