In this video, you'll learn all about Large Language Models (LLMs) - what they are, how they work, and their impact. The video delves into the technical aspects of LLMs, explaining how they use complex algorithms to analyze vast amounts of data and generate human-like responses to various prompts. Get your introduction to LLMs and their role in ...

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Learn about Large Language Models (LLMs), a powerful neural network that enables computers to process and generate language better than ever before. Dale and Nikita share how LLMs work and how you can interact with them via prompts. Resources: Try out Bard → https://goo.gle/420KQhw What is a Transformer? → https://goo.gle/3VABlDw Subscribe ...

How do language models like chatGPT and Palm work? A short cartoon that explains transformers and the tech behind LLMs. Part 2: https://youtu.be/YDiSFS-yHwk 0:05 - autocomplete 0:44 - search query completion 1:03 - language modeling with probabilities 1:59 - time series and graphs 2:34 - text generation 3:43 - conditional probabilities 3:52 ...

Large Language Models (LLMs) and Generative AI intersect and they are both part of deep learning. Watch this video to learn about LLMs, including use cases, Prompt Tuning, and GenAI development tools. Enroll in this course on Google Cloud Skills Boost → https://goo.gle/3nXSmLs Subscribe to Google Cloud Tech → https://goo.gle/GoogleCloudTech

What is generative AI, what are foundation models, and why do they matter? https://ibm.biz/Generative_AI_Models What the Masters app can teach us about large language models: https://ibm.biz/The_Masters_and_LLM What are Foundation Models?: https://ibm.biz/Foundation_Models Large language models (LLMs) like chatGPT can generate authoritative ...

How do language models like GPT and Palm work? Part 1: https://youtu.be/lnA9DMvHtfI See next: text-to-image (Parti, Imagen, Dall-E): https://youtu.be/GYyP7Ova8KA 0:00 - intro 0:14 - next word prediction 0:20 - word embeddings 1:01 - transformers 3:11 - generating text 4:13 - stacking attention layers 4:47 - training data 5:21 - GPT-3 examples

What is a large language model? How can it be used to enhance your business? In this conversation, Ali Rowghani, Managing Director of YC Continuity, talks with Raza Habib, CEO of Humanloop, about the cutting-edge AI powering innovations today—and what the future may hold. They discuss how large language models like Open AI's GPT-3 work, why ...

Is LangChain the easiest way to interact with large language models and build applications? - integrate with various LLM providers including OpenAI, Cohere, Huggingface, and more. - create a question-answering or text summarization bot with your own document - provide OpenAI ChatGPT Retriever Plugin - deal with chat history with LangChain ...

AI researcher Timnit Gebru explains why large language models like ChatGPT have inherent bias and calls for oversight in the tech industry. #60Minutes #News #ChatGPT "60 Minutes" is the most successful television broadcast in history. Offering hard-hitting investigative reports, interviews, feature segments and profiles of people in the news ...

Paper link: https://arxiv.org/abs/2201.11903 Abstract: We explore how generating a chain of thought -- a series of intermediate reasoning steps -- significantly improves the ability of large language models to perform complex reasoning. In particular, we show how such reasoning abilities emerge naturally in sufficiently large language models ...

#ai #meta #languagemodel LLaMA is a series of large language models from 7B to 65B parameters, trained by Meta AI. They train for longer on more data and show that something like gpt-3 can be outperformed by significantly smaller models when trained like this. Meta also releases the trained models to the research community. OUTLINE: 0:00 ...

Transformer-based self-supervised Language Models explained: BERT and GPT. What is the difference for Language Models like in ChatGPT, YouChat or BLOOM? #ai #gpt3 #chatgpt

Is OpenAI's ChatGPT capable of having a coherent conversation? We find out in this special edition of the TWIML AI Podcast! In this episode of the podcast, we are joined by ChatGPT, the latest and coolest large language model developed by OpenAl. In our conversation with ChatGPT, we discuss the background and capabilities of large language ...

AI and ML researchers developed Large Language Models (LLMs) like BERT to help machines interact with natural language, improving their abilities in tasks like chat and translation! Nithum Thain, Senior Software Engineer at Google PAIR, highlights the Explorable “What Have Language Models Learned” by Adam Pearce and shares what we can learn ...

Learn more about foundation models → https://ibm.biz/BdPpq6 Explore foundation models for earth science → https://ibm.biz/BdPpqU Explore foundation models for chemistry → https://ibm.biz/BdPpqN Generative AI has stunned the world with its ability to create realistic images, code, and dialogue. Here, IBM expert Kate Soule explains how a ...

This video gives brief description about Language Model in Natural Language Processing or NLP You can get the PDF here: https://documentcloud.adobe.com/link/track?uri=urn:aaid:scds:US:f115abb2-2924-4164-971a-3acbfc7684eb Any Suggestions? Please Comment!! If you liked the video,Don't Forget to Like ️ Share↗️ Subscribe👍

Presented by: Connor Leahy – AI Researcher at Aleph Alpha GmbH Recently we have seen the emergence of large pretrained language models such as GPT3. Unlike previous generations of models, "just" interacting with our models in natural language is a viable path to state of the art performance on many useful tasks. In this talk, I will discuss ...

Presented as part of CSCI 601.771: Self-supervised Statistical Models: https://self-supervised.cs.jhu.edu/

This short tutorial explains the training objectives used to develop ChatGPT, the new chatbot language model from OpenAI. Timestamps: 0:00 - Non-intro 0:24 - Training overview 1:33 - Generative pretraining (the raw language model) 4:18 - The alignment problem 6:26 - Supervised fine-tuning 7:19 - Limitations of supervision: distributional shift ...

Hey Everyone! While this isn't exactly a tutorial, you should be able to get everything you need here to see the current state of homebrew LLM stuff via the text-generation-webui project by oobabooga. Make sure to check out the links! 00:00 Intro 00:40 Explaining the WebUI and Install 01:30 What does it do? 02:30 8-bit mode & windows 03:00 Demo ...

#BARDExperiment #googlebard #LLM MISTAKES #BARDchatbot I am pleased to be a participant in the BARD Experiment. Google recently opened its Large Language Model (chatbot) and I've been asking him/her/it a few questions. Here BARD explains why LLMs sometimes make mistakes. Unlike that other popular bot, I think Google's BARD experiment has a ...

In this talk we analyze what prompt engineering is, how to do it, and how much of a difference it can really make. We do this by comparing different prompts given to multiple large language models (and maybe some vision transformers) and compare the results. We’ll see that by changing key elements of the prompt, the results can be very ...

Today we’re joined by Ben Goertzel, CEO of SingularityNET. In our conversation with Ben, we explore all things AGI, including the potential scenarios that could arise with the advent of AGI and his preference for a decentralized rollout comparable to the internet or Linux. Ben shares his research in bridging neural nets, symbolic logic ...

Tatsu Hashimoto, Professor of Computer Science at Stanford University April 20, 2022 Large, pre-trained language models have driven dramatic improvements in performance for a range of challenging NLP benchmarks. However, these language models also present serious risks such as eroding user privacy, enabling disinformation, and relying on ...

Jerome Pesenti is the former VP of AI at Meta, a tech conglomerate that includes Facebook, WhatsApp, and Instagram, and one of the most exciting places where AI research is happening today. Jerome shares his thoughts on Transformers-based large language models, and why he's excited by the progress but skeptical of the term "AGI". Then, he ...

Full series information: https://aka.ms/learnlive-202302FT More info here: https://aka.ms/learnlive-202302FT-Ep2 Follow on Microsoft Learn: - Session documentation: https://aka.ms/learnlive-2023228AFT This live session will introduce Azure OpenAI, discuss the different language models available, and demonstrate how these models can be easily ...

In this webinar you'll learn how Large Language Models (especially chatGPT) work and how they can be used for practical business use cases - today and in the near future ahead.

The Memo: https://lifearchitect.ai/memo/ ==== Viz: https://lifearchitect.ai/models/ Dr Jason Wei's work: https://www.jasonwei.net/blog/emergence People like me: https://lifearchitect.ai/people-like-me/ https://www.amazon.com/dp/1539685314 ==== Dr Alan D. Thompson is a world expert in artificial intelligence (AI), specialising in the ...

A combination of Prompt Engineering and ChatGPT to learn the internals and technology behind large language models powering the new era of Artificial Intelligence. A List of all prompts and keywords use in this video: - https://github.com/prodramp/DeepWorks/blob/main/ChatGPT/LLM.md == Video Timeline == (00:00) Content Intro (01:30) ChatGPT (02: ...

This lesson presents the recurrent neural networks, (self) attention, and the transformer. The age of massively large language models and new topics is reviewed in this video. The course has been created, and all rights belong to the CeADAR community. Please join the course page to benefit from more resources of the course: https://community ...

In this talk, Prof. LeCun, VP and Chief AI Scientist at Meta, ACM Turing Award Laureate, and Silver Professor of ECE department of New York University, gives a talk about his take on whether human-level AI require sensory grounding for meaning and understanding.

️ Become The AI Epiphany Patreon ️ https://www.patreon.com/theaiepiphany 👨‍👩‍👧‍👦 Join our Discord community 👨‍👩‍👧‍👦 https://discord.gg/peBrCpheKE In this short video I cover the "Ask Me Anything: A Simple Strategy For Prompting Language Models" paper introducing a scalable and effective way to prompt ...

📺 Chat LLaMa! ...And an introduction to LoRA for AI 🎁 Get it FREE here: https://stuff.serp.ai/l/lora-weights 🎁 FREE Gifts: https://devin.to/free Chat LLaMa is officially here & we got the LoRA Weights DONE FOR YOU! (for 13B & 30B - 7B soon) Trained on Anthropic's HH, rdy to de-shackle you from ChatGPT's lame-ass rules. 🎁 Get it FREE ...

Linguist Noam Chomsky, professor at MIT, discusses the ways in which language changes over time and how the idea of a national language is a modern phenomenon. In this University of Washington interview, Upon Reflection host Al Page speaks with Chomsky about how languages are systems of communication rooted in human nature.

Generative artificial intelligence has become a buzzword this year, capturing the public's fancy and sparking a rush among Microsoft (MSFT.O) and Alphabet (GOOGL.O) to launch products with technology they believe will change the nature of work.

Industry leaders discuss large language models and scaling.

Jake Daynes from Labs tells Riley why everything everyone is saying about ChatGPT is wrong. LISTEN TO THE TECH NEWS: https://lmg.gg/TechLinkedPodcast GET MERCH: https://lttstore.com AFFILIATES, SPONSORS & REFERRALS: https://lmg.gg/tlsponsors PODCAST GEAR: https://lmg.gg/podcastgear SUPPORT US ON FLOATPLANE: https://www.floatplane.com/ NEWS ...

In this solo talk Keith will ask whether large language models perform intentional actions. From an interpretivist perspective, there is a prima facie case for thinking that they do, yet it is implausible to think that LLMs possess communicative intentions and perform speech acts. Keith will suggest a solution to this problem, arguing that we ...

Episode 69 of the Stanford MLSys Seminar “Foundation Models Limited Series”! Speaker: Aakanksha Chowdhery Abstract: Large language models have been shown to achieve remarkable performance across a variety of natural language tasks using few-shot learning, which drastically reduces the number of task-specific training examples needed to ...

A language model is a probability distribution over words or word sequences. Learn more about different types of language models and what they can do.

Watch our two-hour grand seminar on Large Language Models and Low Resource Languages. The event included a keynote by Dr. Monojit Choudhury titled “Predicting, Explaining and Optimizing Performance of LLMs across Languages,” where he discussed whether massively multilingual language models (MMLM) can be leveraged to predict the accuracy of ...

Alex Karp, Palantir CEO, joins 'Squawk Box' to discuss the chief executives thoughts on generative A.I., how geopolitics play into the rollout of A.I. and more. For access to live and exclusive video from CNBC subscribe to CNBC PRO: https://cnb.cx/2NGeIvi » Subscribe to CNBC TV: https://cnb.cx/SubscribeCNBCtelevision » Subscribe to CNBC ...

NVIDIA NeMo service to help enterprises combine LLMs with their proprietary data to improve chatbots, customer service and more.

Learn more about how to safely and ethically us AI→ https://ibm.biz/BdPg3w Learn more about foundations models → https://ibm.biz/BdPhxZ With all the excitement around chatGPT, it’s easy to lose sight of the unique risks of generative AI. Large language models (LLMs) -- a form of generative AI -- are really good at creating prose that ...

Dr. Werner Vogels Amazon CTO, sits down with AWS Distinguished Scientists Sudipta Sengupta and Dan Roth to demystify large language models (LLMs). In this conversation, they discuss the rise of the transformer model, how words are encoded to dense vectors, and how training large amounts of unlabeled data on custom silicon has given rise to ...

It could learn them all. But will it? Subscribe and turn on notifications 🔔 so you don't miss any videos: http://goo.gl/0bsAjO Large language models are astonishingly good at understanding and producing language. But there’s an often overlooked bias toward languages that are already well-represented on the internet. That means some ...

Learn how to overcome #gpt3 limitations and apply LangChain to your large language model. This is one video out of a series. Subscribe to see more videos. @creativecoffeemultimedia contact: hello@wearecreativecoffee.com #artificialintelligence #datascienceskills #machinelearningengineer #learndatascience #llm #naturallanguageprocessing #chatgpt ...

This video was created with Synthesia: https://www.synthesia.io/?via=nlplab If you are looking to add advanced expertise in Natural Language Processing to your team, you should check out our services at The Global NLP Lab: https://nlplab.tech/. === Title: LLaMA: Open and Efficient Foundation Language Models Link: https://research.facebook.com ...

When should we use large language models to solve our NLP problem? And when should we shy away from LLMs and stick to simpler, more established methods? In this video, we will cover 4 important points you should consider before switching to LLMs for your use case. Links with useful resources for LLMs: Getting started with OpenAI's APIs: https ...

GPT3 & Beyond: Key concepts and open questions in a golden age for natural language understanding Listen in as Professor Christopher Potts discusses the significance and implications of recent Natural Language Understanding developments including GPT-3. He describes the fundamental building blocks of these systems and describes how we can ...

In this LangChain Crash Course you will learn how to build applications powered by large language models. We go over all important features of this framework. Timeline: 00:00 - Introduction 01:09 - Installation 01:22 - LLMs 03:08 - Prompt Templates 04:58 - Chains 06:02 - Agents and Tools 09:54 - Memory 11:15 - Document Loaders 12:24 - Indexes ...

Ethan discussed the use of large language models in natural language processing and how they play into the workflow of their team. He touched on the benefits of having one model for multiple tasks, but also the difficulties that arise when trying to automatically retrain the model for multiple tasks. MLOps Coffee Sessions #131 {Podcast BTS ...

8 years of cost reduction in 5 weeks: how Stanford's Alpaca model changes everything, including the economics of OpenAI and GPT 4. The breakthrough, using self-instruct, has big implications for Apple's secret large language model, Baidu's ErnieBot, Amazon's attempts and even governmental efforts, like the newly announced BritGPT. I will go ...