Deep Thought RSS

AI, Synthetic Intelligence -

Making Chat (ro)Bots

Making Chat (ro)Bots
We created a robot tour guide using Spot integrated with Chat GPT and other AI models as a proof of concept for the robotics applications of foundational models. Learn more: https://bostondynamics.com/blog/robots-that-can-chat/ Project Team: Matt Klingensmith Michael Macdonald Radhika Agarwal Chris Allum Rosalind Shinkle #BostonDynamics #chatgpt 00:00: Introduction 01:08: Making Chat (ro)Bots 01:39: Precious Metal Cowgirl 02:38: A Robot Tour Guide 03:07: How does it work? 04:19: Shakespearean Time Traveler 04:36: Creating Personalities 04:54: "Josh" 05:23: Lateral Thinking 06:03: Teenage Robot 06:43: Nature Documentary 07:32: What's next?

Read more

AI, Synthetic Intelligence -

Graph ML: Build Knowledge Graphs using Generative AI and LLMs

Graph ML: Build Knowledge Graphs using Generative AI and LLMs
Knowledge Graphs Generative AI, LLMs Graph DBs Neo4j Cypher Fine Tune LLMs Graph ML Node Embeddings Graph Features Langchain Chatbots Gradio Code: https://github.com/neo4j-partners/neo4j-generative-ai-google-cloud/tree/a3632f657981db1f90281d0fb9b8a7c676f55e74 #datascience #machinelearning #deeplearning #datanalytics #predictiveanalytics #artificialintelligence #generativeai #largelanguagemodels #naturallanguageprocessing #computervision #transformers #embedding #graphml #graphdatascience #datavisualization #businessintelligence #montecarlosimulation #simulation #optimization #python #aws #azure #gcp

Read more

AI, Synthetic Intelligence -

AI agent + Vision = Incredible

AI agent + Vision = Incredible
A step by step tutorial of how to build vision powered AI agent via autogen + llava + stable diffusion AND Break down of 160-page analysis of GPT4V capabilities 🤘 Get 15% off on sceneXplain via my code AIJASON : https://go.jina.ai/scenexplainjason 🔗 Links - Follow me on twitter: https://twitter.com/jasonzhou1993 - Join my AI email list: https://www.ai-jason.com/ - My discord: https://discord.gg/eZXprSaCDE - sceneXplain: https://go.jina.ai/scenexplainjason - Vision-agent Github: https://github.com/JayZeeDesign/vision-agent-with-llava ⏱️ Timestamps 0:00 Intro 1:15 What is multi-modal model 2:12 GPT4V ability break down 4:34 sceneXplain 6:00 Visual prompt techniques 10:53 Use cases 13:00 Build vision agent #1 - Setup 14:20 Build vision agent #2 - Use Llava model 15:58 Build vision agent #3 - Use Stable diffusion 16:52 Build vision agent #4 - Set agent system via autogen 18:53 Build vision agent #5 - Demo 👋🏻 About Me My name is Jason Zhou, a product designer who shares interesting AI experiments & products. Email me if you need help building AI apps! ask@ai-jason.com #gpt4 #autogen #autogpt #ai #artificialintelligence #tutorial #stepbystep #openai #llm #chatgpt #largelanguagemodels #largelanguagemodel #bestaiagent #chatgpt #agentgpt #agent #babyagi #llava #stablediffusion

Read more

AI, Synthetic Intelligence -

How AI Will Change the Music Industry Forever w/ will.i.am | EP #70

How AI Will Change the Music Industry Forever w/ will.i.am | EP #70
This is a clip from the Abundance360 Summit I host in March every year. Abundance360 is a group of ~400 successful entrepreneurs who are interested in using their resources to uplift humanity. You can learn more about the membership here: https://www.abundance360.com/ —-------- In this episode, recorded during this year Peter’s Executive Summit, Abundance360, Peter and Keith Ferrazzi discuss with will.i.am the implications of artificial intelligence (AI) on creativity, ownership, and the human experience. Will.i.am is a multi-faceted artist, entrepreneur, and philanthropist best known as a founding member of the Grammy-winning group The Black Eyed Peas. Beyond his music career, he's a passionate advocate for STEAM (Science, Technology, Engineering, Arts, and Math) education and has made significant strides in the tech industry with various innovations. His visionary approach seamlessly blends creativity with technology, making him a prominent figure in both the entertainment and tech sectors. Download Will.I.Am’s new app for creatives: https://fyi.fyi/index.html Learn more about my executive summit, Abundance360: https://www.abundance360.com/ —-------- This episode is supported by exceptional companies: Get started with Fountain Life and become the CEO of your health: https://fountainlife.com/peter/ Use my code MOONSHOTS for 25% off your first month's supply of Seed's DS-01® Daily Synbiotic: seed.com/moonshots —-------- Topics: 0:00 - Intro 1:33 - will.i.am on AI: Surprising Perspectives 2:15 - A Futurist Legend: Dean Kamen 3:44 - Embrace Your Embarrassment 4:14 - Will's Creative Philanthropy 8:21 - Uniting Creativity and Technology 13:57 - Tech Transforms Scarcity into Abundance 16:02 - Bridging Digital Divides Together 24:39 - Dreaming Out of a Nightmare 31:05 - Life-Enhancing Diagnostics and Therapeutics 33:25 - AI & Human Empathy 40:56 - AI and Healthcare Ethics 43:55 - The Life-Impacting Work of Will Marshall 49:49 - Exponential Tech: What Future? 52:41 - Transforming Communities Through Empowerment 56:52 - Kids Need Smart Education Now 1:00:45 - Combating AI Bias with Humanity 1:02:56 - Creating Without Judgment -------------------------------------------- I send weekly emails with the latest insights and trends on today’s and tomorrow’s exponential technologies. Stay ahead of the curve, and sign up now: https://www.diamandis.com/subscribe My new book with Salim Ismail, Exponential Organizations 2.0: The New Playbook for 10x Growth and Impact, is now available on Amazon: https://bit.ly/3P3j54J Get my new Longevity Practices book for free: https://www.diamandis.com/longevity Connect with Peter: Twitter: https://bit.ly/40JYQfK Instagram: https://bit.ly/3x6UykS Listen to the show: Apple: https://apple.co/3wLXeV3 Spotify: https://spoti.fi/3DwLzgs

Read more

AI, Synthetic Intelligence -

“What's wrong with LLMs and what we should be building instead” - Tom Dietterich - #VSCF2023

“What's wrong with LLMs and what we should be building instead” - Tom Dietterich - #VSCF2023
Thomas G. Dietterich is emeritus professor of computer science at Oregon State University. He is one of the pioneers of the field of machine learning. He served as executive editor of the journal called Machine Learning (1992–98) and helped co-found the Journal of Machine Learning Research. He is one of the members of our select valgrAI Scientific Council. Keynote: “What's wrong with LLMs and what we should be building instead” Abstract: Large Language Models provide a pre-trained foundation for training many interesting AI systems. However, they have many shortcomings. They are expensive to train and to update, their non-linguistic knowledge is poor, they make false and self-contradictory statements, and these statements can be socially and ethically inappropriate. This talk will review these shortcomdifferentings and current efforts to address them within the existing LLM framework. It will then argue for a , more modular architecture that decomposes the functions of existing LLMs and adds several additional components. We believe this alternative can address all of the shortcomings of LLMs. We will speculate about how this modular architecture could be built through a combination of machine learning and engineering. Timeline: 00:00-02:00 - Introducción 00:00-02:00 Introduction to large language models and their capabilities 02:01-3:14 Problems with large language models: Incorrect and contradictory answers 03:15-4:28 Problems with large language models: Dangerous and socially unacceptable answers 04:29-6:40 Problems with large language models: Expensive to train and lack of updateability 06:41-12:58 Problems with large language models: Lack of attribution and poor non-linguistic knowledge 12:59-15:02 Benefits and limitations of retrieval augmentation 15:03-15:59 Challenges of attribution and data poisoning 16:00-18:00 Strategies to improve consistency in model answers 18:01-21:00 Reducing dangerous and socially inappropriate outputs 21:01-25:26 Learning and applying non-linguistic knowledge 25:27-37:35 Building modular systems to integrate reasoning and planning 37:36-39:20 Large language models have surprising capabilities but lack knowledge bases. 39:21-40:47 Building modular systems that separate linguistic skill from world knowledge is important. 40:48-45:47 Questions and discussions on cognitive architectures and addressing the issue of miscalibration. 45:48 Overcoming flaws in large language models through prompting engineering and verification. Follow us! LinkedIn: https://www.linkedin.com/company/valgrai/ Instagram: https://www.instagram.com/valgrai/ Youtube: https://www.youtube.com/@valgrai/ Twitter: https://twitter.com/fvalgrai

Read more

Tags
#WebChat .container iframe{ width: 100%; height: 100vh; }