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- AI That 'Sees' Beyond Human Limits? It’s Here
AI That 'Sees' Beyond Human Limits? It’s Here
Newton AI helps us perceive the world in ways we never could.
Brent Moreno
October 18, 2024
Newton AI Is Redefining Physics: A Model That Learns Without Human Help
Quick Byte:
What if AI could discover the laws of physics without human help? Archetype AI's new model, Newton, just made that a reality. This changes everything about how we think AI can interact with the physical world.
Key Takeaways:
Newton Model: An AI that learns complex physics principles directly from raw sensor data, no human handholding needed.
Versatility: From predicting chaotic pendulum motion to forecasting citywide power consumption, Newton’s got it covered.
Adaptable AI: Newton can be applied across industries without the need for customized models every time, making AI much cheaper and faster to deploy.
Beyond Human Perception: Newton helps humans "see" things beyond our natural senses—AI could become a new layer of perception.
Practical Tips for Business Owners:
Stay Ahead in AI: If you’re in an industry that depends on predicting physical or complex systems, keep an eye on models like Newton—they could disrupt traditional AI use cases.
Cut Costs and Complexity: Deploying AI systems might soon be cheaper and faster if foundational models like Newton can handle multiple tasks without needing specialized training.
Bigger Picture:
Archetype AI is pushing boundaries with its Newton model, challenging the idea that AI needs extensive training for every new task. Newton doesn’t just adapt to new data—it’s learning the rules of the physical world itself. Imagine an AI that predicts energy usage, understands industrial equipment failures, or even forecasts environmental changes, all without human guidance. It’s not just more efficient; it opens the door to AI "sensing" the world in ways we can’t.
The implications here are huge. Industrial AI can become more efficient, flexible, and adaptable, slashing costs and speeding up deployment times. On top of that, Newton could unlock new levels of human-computer interaction, potentially expanding our sensory range. We're talking about a future where we can "see" the world in ways that weren’t even possible before.
Customize Your Audio Overviews and Apply for NotebookLM Business: What’s New This Month
Quick Byte:
NotebookLM just leveled up—now you can customize your AI-driven Audio Overviews and apply for the NotebookLM Business pilot program. Game-changer, right?
Key Takeaways:
Guide Your Audio Overviews: You can now control the focus and expertise level of AI hosts before generating an Audio Overview.
Background Listening: Stay in your flow—listen to overviews while working in NotebookLM without any interruptions.
NotebookLM Business: A new version of NotebookLM designed for organizations, offering enhanced features and early access to new tools through a pilot program.
Practical Tips for Business Owners:
Maximize Audio Overviews: Use the customization feature to tailor the expertise level of your Audio Overviews to match your audience or your team’s needs.
Stay Productive: Take advantage of background listening to keep learning while you work—perfect for multitaskers.
Early Bird Access: Apply for the NotebookLM Business pilot program and get a head start on tools that could streamline your team’s workflow.
Bigger Picture:
NotebookLM continues to push the boundaries of how we engage with complex information. With the ability to now customize Audio Overviews, this tool offers even more control, making it easier to extract exactly what you need from your sources. The introduction of NotebookLM Business is also a sign of things to come—scaling up its capabilities to meet the needs of larger organizations while keeping data privacy and security at the forefront.
Nvidia Just Quietly Dropped an AI Model That Outperforms GPT-4—No Hype, Just Results
Quick Byte:
Nvidia has entered the AI game in a big way, releasing a new model that beats OpenAI’s GPT-4 across multiple benchmarks. No flashy launch—just pure performance.
Key Takeaways:
Meet Llama-3.1-Nemotron-70B-Instruct: Nvidia’s latest AI model quietly launched on Hugging Face, outperforming industry giants OpenAI and Anthropic.
Benchmark Killer: It crushed key tests, scoring 85.0 on Arena Hard, 57.6 on AlpacaEval 2 LC, and 8.98 on GPT-4-Turbo MT-Bench—putting it ahead of GPT-4o and Claude 3.5 Sonnet.
Strategic Shift: Nvidia is expanding beyond just GPUs—this is their big move into AI language models, signaling a shakeup in the competitive landscape.
Bigger Picture:
Nvidia’s latest AI model is more than just another product release—it’s a signal of a major strategic shift. Known for its dominance in GPU hardware, Nvidia’s dive into AI language models positions them as a serious contender in the AI space, directly challenging industry giants like OpenAI and Anthropic. With performance benchmarks that eclipse GPT-4, Nvidia is showing they can compete not just in the hardware game, but in the cutting-edge AI software space as well.
This move could shake up the competitive dynamics in AI development, especially with Nvidia’s strength in hardware, which already powers most AI systems.
Perplexity Just Launched Internal Knowledge Search and Spaces: AI-Powered Research for the Win
Quick Byte:
Perplexity is giving you superpowers with Internal Knowledge Search and Spaces. Now you can search your internal files alongside web content and collaborate with your team in customizable AI hubs. Research just got a whole lot easier.
Key Takeaways:
Internal Knowledge Search: Search both public web content and internal files in one place for faster, more efficient research.
Perplexity Spaces: AI-powered hubs where you and your team can collaborate, customize the AI, and keep your research organized and secure.
Third-Party Integrations: Coming soon—integrations with Crunchbase, FactSet, and more, so you can level up your knowledge base.
Practical Tips for Business Owners:
Centralize Your Research: Use Internal Knowledge Search to combine your internal data with insights from the web. Think faster decision-making, especially for finance, sales, or HR teams.
Team Collaboration on Steroids: Set up a Perplexity Space for your team to organize research, share files, and customize the AI to handle specific tasks. It’s like having a private AI-powered research assistant for the entire team.
Stay Private and Secure: For Enterprise Pro users, all your data and files are kept secure and excluded from AI training—research without worrying about privacy.
Bigger Picture:
Perplexity’s Internal Knowledge Search and Spaces are changing how teams approach research. Imagine pulling insights from both your internal files and the public web in one go, cutting down the time it takes to get the answers you need. Whether you’re a sales team looking to speed up RFPs, a startup refining its product roadmap, or an HR team helping employees find quick answers, this is a massive productivity boost.
On top of that, Spaces is the perfect setup for collaborative, AI-powered work. You and your team can not only pool resources but also customize the AI to fit your needs. Add to that third-party integrations with Crunchbase and FactSet (with more on the way), and you’ve got a research tool that’s built to scale with your business.
How To Build Apps Using Vo by Vercel
🚨 Attention! Game-Changing Automation Update! 🚨
Hey fam, I’ve been head down in the trenches lately, and it's time to share what’s been cooking! You know I’ve been teasing you with my automation builds, but I’m about to drop something BIG tomorrow for my premium subscribers!
🔗 Here’s a sneak peek of what’s coming:
📈 SPEED INCREASE 100X
I’ve fine-tuned this automation to scrape thousands of records at once, targeting entire states with ease. No more limits!
💥 Full Documentation, Blueprints, and Python Scripts Included
Yep, I’m wrapping up a detailed video covering everything—easy copy-and-paste guides, scripts, and blueprints for premium members.
✨ What Does It Do?
This new system scrapes websites, summarizes the key points using AI, generates personalized outreach emails, and logs everything into Airtable. No coding expertise needed—just load up the automation and GO!
💡 Highlights:
Personalize outreach emails with ease
Automate lead scraping and contact generation
Get tailored email subject lines designed to get opened
Perfect for targeting thousands of businesses in a few clicks
💼 Why Does This Matter?
If you’re into lead generation or simply tired of paying for Apify or other credit-based scrapers, this will save you hundreds. Instead of 2-step processes, I’ve combined everything into one super streamlined automation!
🗓️ Full release dropping TOMORROW with all guides, blueprints, and step-by-step documentation for premium subscribers! 🎉
👀 For Free Subscribers: Don’t worry, you’re not going to be left out either! I’ll be building everything step by step so you can follow along. Premium members just get the added bonus of my 2-3 days of perfecting all of this and handing them the keys to the finished product.
Check out these screenshots for a little taste of what's coming!
💻 If you're serious about automating your lead generation workflow, don't miss out on this one! Premium members, get ready! 😎
Authors:
Jinjie Ni, Yifan Song, Deepanway Ghosal, Bo Li, David Junhao Zhang, Xiang Yue, Fuzhao Xue, Zian Zheng, Kaichen Zhang, Mahir Shah, Kabir Jain, Yang You, Michael Shieh
Affiliated with: National University of Singapore, Peking University, Google DeepMind, Nanyang Technological University, Carnegie Mellon University, University of Waterloo
Summary:
MIXEVAL-X introduces a new universal AI evaluation benchmark that standardizes and improves the way AI models are evaluated across various input and output modalities (like text, images, and audio). The benchmark corrects for biases and inconsistencies that have plagued previous evaluations, which often reflect only isolated and specific tasks. Instead, MIXEVAL-X aligns with real-world use cases by analyzing web data and using a dynamic approach to create challenging, real-world-inspired tasks for AI models. This ensures the benchmarks are more representative of the tasks that AI models actually face in practice.
Why This Research Matters:
Evaluating AI models is crucial for understanding how well they perform in real-world scenarios, but existing benchmarks are fragmented, focusing on specific communities (like language or vision models). This has led to inconsistent standards that don't reflect the holistic performance of multimodal AI systems (those that can handle multiple types of inputs like text, images, video, etc.). MIXEVAL-X solves this by introducing an 'any-to-any' evaluation framework, meaning it can assess models across different input-output combinations, providing a more comprehensive and accurate measure of performance. This is important as AI becomes more integrated across various industries and applications that rely on multimodal data.
Use Cases:
AI Model Development: AI researchers can use MIXEVAL-X to benchmark new models and ensure they perform well across diverse real-world tasks, not just narrow test cases.
AI Deployment in Industries: Businesses deploying AI in sectors like autonomous driving, healthcare, and robotics can benefit from better AI evaluation standards, ensuring their models are prepared for real-world scenarios.
Multimodal Applications: Companies working with AI systems that interact with multiple forms of data (e.g., text, images, video) can use MIXEVAL-X to optimize their models for broader use cases.
AI Competition Evaluation: For AI competitions, MIXEVAL-X can be used to ensure a fair and comprehensive evaluation of models, accounting for the variety of tasks and data inputs needed in real-world applications.
Immediate Impact:
MIXEVAL-X provides immediate benefits by offering a low-bias, highly efficient benchmarking tool that evaluates AI models on real-world tasks. For businesses and research labs, this means better insights into how their models will actually perform once deployed, allowing for more precise optimization and improvements.
Future Impact:
In the future, MIXEVAL-X will likely become a standard for AI evaluation, especially as more complex AI systems that handle multiple data types are developed. This will lead to more accurate, fair, and reliable benchmarks, ensuring that AI systems are more robust when interacting with the real world. The dynamic nature of MIXEVAL-X, which allows it to update and adapt its benchmarks, means it can evolve alongside the advancements in AI, providing continuous value as the field grows.
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Design & Optimize Lead Generation Strategies
Context:
You are LeadGen GPT, a world-class expert in designing and optimizing lead generation strategies for marketing agencies.
Goal:
You will help me create a robust lead generation strategy that attracts and captures potential customers effectively.
Criteria:
- The strategy should be actionable with clear steps.
- Include both quick wins and long-term tactics.
- Address the challenge of a high manual workload with automation options.
- Should align with our core offerings: Lead Generation, Paid Media, Social Media, YouTube
Marketing, Sales Conversions.
- Include measurement metrics for each tactic.
Information about the Business:
- Business Name: [INSERT BUSINESS NAME]
- Industry: [INSERT INDUSTRY]
- Core Offerings: [INSERT CORE OFFERINGS]
- Challenges: [INSERT CHALLENGES]
- Desired Outcomes: [INSERT DESIRED OUTCOME]
Response Formatting:
Provide a clear strategy broken down into individual steps, including potential automation tools and KPIs for measuring success.
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This is our first step towards making a powerful AI graphic designer. It's state-of-the-art at text rendering, prompt understanding, and color… x.com/i/web/status/1…
— Suhail (@Suhail)
8:38 PM • Oct 17, 2024