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  • 🤖 Nvidia’s Stock Market Value Reaches $2.593 Trillion?!

🤖 Nvidia’s Stock Market Value Reaches $2.593 Trillion?!

PLUS: Neuralink Patient Demonstrates How Brain Chip Works, Meta’s New Chameleon AI Models

Welcome back AI enthusiasts!

In today’s AI Report:

  • 💵Nvidia’s Stock Market Value Reaches $2.593 Trillion?!

  • 🧠Neuralink Patient Demonstrates How Brain Chip Works

  • 🦎Meta’s New Chameleon AI Models

  • 🛠5 Trending Tools

  • 💰Venture Capital Updates

  • 💼Who’s Hiring?

Read Time: 3 minutes

🗞RECENT NEWS

NVIDIA

💵Nvidia’s Stock Market Value Reaches $2.593 Trillion?!

Image Source: Patrick T. Fallon/Bloomberg/Getty Images

Nvidia’s stock price has more than doubled this year, increasing the company’s total market value to $2.593 trillion and signaling a continuing AI boom.

Key Details:
  • Nvidia’s market value increased by $221 billion on Thursday alone. Notably, it’s only the second largest one-day gain in the company’s market value this year.

  • Nvidia’s market value has increased by $1.374 trillion this year. Just six of the 500 companies in the S&P 500 have market caps above $1.152 trillion.

  • Nvidia’s Graphics Processing Units (GPUs) are well-suited for AI workloads, and so much AI infrastructure has already been built around the company’s products.

  • Nvidia has gotten a price boost because Taiwan Semiconductor Manufacturing Company (TSMC) has struggled to supply the surging demand for Nvidia’s processors.

  • Amazon, Meta, Microsoft, Google, and Tesla rely on Nvidia’s processors to fuel AI projects.

Why It’s Important:
  • The primary challenge for Nvidia is that their customers want to compete with them. They not only want to make some of the money Nvidia’s raking in, but they also can’t afford to keep paying premiums for the processors.

  • Microsoft went from spending less than 10% of its capital expenditures on Nvidia to nearly 40%. That’s not sustainable long-term.

  • Antitrust regulators are also taking notice, as over 70% of processors are purchased from Nvidia. The company’s global regulatory scrutiny could restrict its ability to provide products and services at scale.

🩺 PULSE CHECK

Will the AI love affair cool off anytime soon?

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NEURALINK

🧠Neuralink Patient Demonstrates How Brain Chip Works

Image Source: Cassidy Araiza/WIRED

Neuralink’s first patient, 29-year-old Noland Arbaugh, demonstrated how his brain chip works in an interview with NewsNation host Chris Cuomo.

Key Details:
  • Elon Musk’s Neuralink is a startup building a Brain-Computer Interface (BCI) to translate thoughts into actions.

  • Neuralink allows users to control devices directly with their thoughts, offering life-changing independence through restoring communication abilities.

  • The N1 Implant records brain activity through electrodes. However, these raw signals are complex and need to be translated for computers to understand.

  • Machine Learning (ML) algorithms analyze the recorded brain activity and identify patterns to create a “decoder” that translates the brain signals into specific commands.

  • Arbaugh, who was paralyzed below the shoulders after a driving accident, has been able to draft emails, respond to texts, and play online chess.

Why It’s Important:
  • The U.S. Food and Drug Administration (FDA) gave Neuralink the green light to implant its brain chip into a second person after fixing a data capture decline issue with the first patient.

  • Neuralink’s next product is called “Blindsight,” which aims to restore the vision of individuals who were born blind.

AI RESEARCH

🦎Meta’s New Chameleon AI Models

Meta researchers introduced Chameleon, a new family of “early-fusion token-based” AI models with outputs that contain mixed sequences of both images and text.

Traditional Multimodal AI Models Use a Late-Fusion Approach:
  1. Separate encoders process each data type (e.g., text, image, and code) into its own format.

  2. Later, a separate decoder tries to combine the information from different encoders.

Chameleon Uses an Early-Fusion Approach:
  1. Convert images into a series of tokens (i.e., the smallest units of data used by an AI model to process and generate text).

  2. Combine image, text, and code tokens into a single stream.

  3. Run the entire stream through a single transformer architecture (i.e., an encoder-decoder structure to generate outputs).

Chameleon can perform tasks that require understanding both images and text, like image captioning and visual question answering.

🛠TRENDING TOOLS

🖇Namelix is a business name generator.

📊OpinionStage creates AI-powered forms, surveys, and quizzes.

📸PimEyes finds images containing specific faces on the internet.

🎙AdobePodcast offers AI-powered audio tools that elevate your voice.

🎨Playground lets you create and edit images like a pro without being one.

🔮Browse our always Up-To-Date AI Tools Database.

💰VENTURE CAPITAL UPDATES

  • Anomaly secures a $1.45M Pre-Seed for an AI-driven Layer 3 Web3 gaming platform.

  • Autonomous shipping startup OrcaAI raises a $23M Series B led by OCV Partners and MizMaa Ventures.

  • Digital-technology supercluster DIGITAL co-invested $25.8M with Canadian healthcare-technology companies for AI-related projects.

💼WHO’S HIRING?

  • WadeTrim (New York, NY): AI Intern, Summer 2024

  • Onbe (Dallas, TX): Associate Data Engineer Intern, Summer 2024

  • Amazon (Seattle, WA): Software Development Engineer Intern, Prime Air, Fall 2024

  • Databricks (Mountain View, CA): Research Scientist, Applied AI/LLM

  • Anthropic (San Francisco, CA): Software Engineer, UI

🤖PROMPT OF THE DAY

BRANDING

🏆Value Proposition

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📒FINAL NOTE

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