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Apple's AI Chatbot 🍎, Tesla's Dojo Supercomputers 💾, and Meta Cancels its Quest Pro 🥽

The Morning Brief

In Today’s Edition:

Apple tests a ChatGPT-like AI chatbot, Tesla's driverless Dojo supercomputers enter production, and Meta cancels its Quest Pro project. Nasdaq pauses crypto custody plans, Massachusetts tests face recognition, and new AI supercomputers power up.

Stay informed with today's top metaverse tech stories and gain access to over 15 quick bytes, research papers, tools, guides, and resources to help you navigate the metaverse.

👇 Must-reads

  1. Apple Tests ChatGPT-like AI Chatbot: Apple is reportedly testing a new AI chatbot that closely resembles OpenAI's ChatGPT. The new chatbot is designed to provide more accurate and context-aware responses, making it a potentially powerful tool for customer service and other applications. (TechCrunch)

  2. Tesla's Driverless Dojo Supercomputers in Production: Tesla has begun production of its Dojo supercomputers, which are designed to power its driverless cars. The supercomputers are expected to significantly enhance the capabilities of Tesla's autonomous vehicles. (The Verge)

  3. Meta Quest Pro Cancelled: Meta has reportedly cancelled its Quest Pro project. The company has not provided any specific reasons for the cancellation, but it is speculated that it may be due to technical or market-related challenges. (Mixed News)

  4. Nasdaq Pauses Crypto Custody Services: Nasdaq has put its plans to launch crypto custody services on hold. The decision comes amid regulatory uncertainties and concerns about the potential risks associated with the crypto market. (CNBC)

  5. Massachusetts Tests Face Recognition: Massachusetts is conducting a pilot program to test the use of face recognition technology by police. The program aims to assess the technology's effectiveness and its potential impact on privacy and civil liberties. (MIT Technology Review)

  6. AI Supercomputer Powered by Giant Chips: A new AI supercomputer has been brought to life, powered by giant computer chips. The supercomputer is expected to significantly enhance the capabilities of AI systems and open up new possibilities in various fields. (The New York Times)

  7. AI Interoperability between Meta's Llama and Microsoft's ChatGPT: Meta and Microsoft are working on making their AI models, Llama and ChatGPT, interoperable. This move could lead to more powerful and versatile AI systems in the future. (The Verge)

  8. Microsoft Teams Integrates 365 Copilot AI Chat: Microsoft Teams has integrated the 365 Copilot AI chat into its platform. The AI chat is designed to assist users in various tasks, making Teams more versatile and user-friendly. (The Verge)

  9. Ethereum Co-founder Teases Game-changing Upgrade: Ethereum co-founder has teased a new upgrade that could be a '100x game-changer'. The upgrade is expected to significantly enhance the capabilities and efficiency of the Ethereum network. (Forbes)

  10. OpenAI Holds Back GPT-4 Image Features: OpenAI is reportedly holding back the image features of its GPT-4 model due to privacy concerns. The decision underscores the challenges of balancing the capabilities of AI systems with the need to protect user privacy. (Ars Technica)

🦄 Startups & Venture Capital

  1. SAP Invests in Generative AI Startups Anthropic, Cohere, and Aleph Alpha: SAP has invested in three generative AI startups, Anthropic, Cohere, and Aleph Alpha. The investment aims to accelerate the development of AI technologies and applications, particularly in the field of natural language processing and understanding. (TechCrunch)

  2. Nous Co. Uses Generative AI for Household Bills: Nous Co. has integrated generative AI into its platform to help users manage their household bills. The AI system analyzes users' spending habits and suggests ways to reduce costs, leading to significant savings for many users. (TechCrunch)

  3. Gushwork.ai Raises $2.1M for AI-Powered Business Process Outsourcing: Gushwork.ai, a platform that combines AI and human expertise to advance business process outsourcing, has raised $2.1 million in pre-seed funding. The startup provides a marketplace featuring offshore workers trained in using various AI applications to help businesses carry out their processes efficiently. (TechCrunch)

✨ Quick Bytes

Academic Research Papers

  1. DreamTeacher: Pretraining Image Backbones with Deep Generative Models: This study introduces DreamTeacher, a framework for self-supervised feature representation learning that employs generative networks to pre-train image backbones. Two types of knowledge distillation are explored: distilling generative features onto target image backbones instead of pre-training them on labeled datasets like ImageNet, and distilling labels obtained from generative networks onto logits of target backbones. Extensive analyses on multiple generative models, dense prediction benchmarks, and various pre-training regimes demonstrate that DreamTeacher outperforms existing self-supervised representation learning approaches. Unsupervised ImageNet pre-training with DreamTeacher shows significant improvements over ImageNet classification pre-training on downstream datasets, indicating the potential of generative models, particularly diffusion generative models, for representation learning on large, diverse datasets without manual annotation.

  2. NotebookLM: Google’s Experimental AI Notebook for Enhanced Learning and Insight: Google has introduced NotebookLM, an experimental AI-powered notebook designed to help users learn and make connections faster. It leverages language models to summarize facts, explain complex ideas, and generate new connections based on selected sources. Unlike traditional chatbots, NotebookLM can be "grounded" in your own notes and sources, creating a personalized AI assistant knowledgeable in your relevant information. Users can upload Google Docs, receive document summaries, ask questions, and generate ideas. While NotebookLM reduces the risk of incorrect information, fact-checking against original sources is still important, and the AI provides citations for easy verification.

  3. Meet Lamini AI: A Revolutionary LLM Engine Empowering Developers to Train ChatGPT-level Language Models with Ease: Lamini, an LLM (Large Language Model) platform, has been introduced to enable developers to train high-performing LLMs easily. It aims to simplify the process of training LLMs by providing optimized prompt-tuning and fine-tuning capabilities. The platform allows developers to run multiple base model comparisons, generate datasets for instruction-following LLMs, and fine-tune base models on large datasets. Lamini combines the ease of prompt-tuning with the performance of reinforcement learning from human feedback (RLHF) and fine-tuning. It also offers a data generator for creating instruction-following datasets and provides an open-source LLM fine-tuned using Lamini. The goal is to make LLM training more accessible and efficient, empowering engineering teams to leverage the power of generative AI.

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