🤖 Meta Releases Llama 4?!

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In today’s Daily Report:

• 🦙Meta Releases Llama 4?!

• ⛏️AI Teaches Itself to Mine Diamond Ore in Minecraft

• 🛠Trending Tools

• 🥪Brief Bites

• 💰Funding Frontlines

• 💼Who’s Hiring?

Read Time: 3 minutes

🗞RECENT NEWS

META

🦙Meta Releases Llama 4?!

Meta just released Llama 4, a family of three new multimodal AI models designed to offer industry-leading performance in text and image understanding.

Key Details:

• Here’re five key terms you need to know:

  1. Tokens: The smallest units of data used to process and generate text.

  2. Multimodal AI Models: Can process, analyze, and generate text, images, audio, video, or code.

  3. Context Window: The amount of tokens a multimodal AI model can consider or “remember” when generating outputs.

  4. Parameters: Internal settings like weights and biases that help multimodal AI models understand and predict words.

  5. Mixture of Experts (MoEs): Multiple smaller AI models that act as “mini-experts” in different domains to tackle different parts of complex problems at the same time.

• The three new multimodal AI models include:

  1. Llama 4 Scout: 17 billion active parameters equipped with 16 MoEs and a 10 million token context window. It runs on a single NVIDIA H100 Tensor Core GPU.

  2. Llama 4 Maverick: 17 billion active parameters equipped with 128 MoEs and a 1 million token context window. It runs on the NVIDIA DGX H100.

  3. Llama 4 Behemoth: 228 billion active parameters with 16 MoEs. It’s expected to outperform OpenAI’s GPT-4.5 and Anthropic’s Claude 3.7 Sonnet in Science, Technology, Engineering, and Mathematics (STEM).

Why It’s Important:

• “We’re gonna share more about Llama 4 Reasoning soon,” said Meta CEO Mark Zuckerberg. He’s referring to Meta’s version of a Reasoning Engine that’ll mimic a human’s decision-making capabilities.

• Llama 4 Maverick achieved 69.8% accuracy on the Graduate-Level Google-Proof Q&A (GPQA) Diamond benchmark, which involves 448 multiple-choice questions crafted by domain experts in biology, physics, and chemistry. For context, Google’s Gemini 2.0 Flash achieved 60.1% accuracy, and OpenAI’s GPT-4o (“o” for “omni”) achieved 53.6% accuracy.

🩺 PULSE CHECK

AI RESEARCH

⛏️AI Teaches Itself to Mine Diamond Ore in Minecraft

Google DeeMind developed “DreamerV3,” an AI System that autonomously learned to mine Diamond Ore in Minecraft without any human intervention in just nine days.

Key Details:

• In Minecraft, players explore a virtual 3D world containing a variety of terrains, including forests, mountains, deserts, and swamps. They use the virtual 3D world’s resources to collect items like oak logs, sandstone, and diamond ore to create objects like chests, fences, and swords.

• “DreamerV3” wasn’t given any step-by-step instructions by humans. Instead, it was encouraged to explore the virtual 3D world and absorb information to identify potential actions.

• For example, “DreamerV3” observed that chopping down oak trees located in forests yielded oak logs. This observation established an essential relationship between an action and the consequence of that action.

• “DreamerV3” leveraged Reinforcement Learning (RL), which mimics the “trial-and-error” process humans use to learn, where actions that lead to desired outcomes are reinforced.

Why It’s Important:

• The 3D virtual world was reset every 30 minutes, forcing “DreamerV3” to adapt to a new randomly generated environment. Despite these constant changes, “DreamerV3” rapidly improved.

• “You must really understand what’s in front of you; you can’t just memorize a specific strategy,” said Google DeepMind Research Scientist Danijar Hafner. “It forces the AI System to self-improve over time.”

🛠TRENDING TOOLS

🔍Genspark is an AI Agent-Powered search engine.

⚙️HeroUI Chat turns brief text prompts into React apps.

✨beautiful.ai generates workplace-ready presentations.

🗳️Voicepanel is an AI Agent that collects customer feedback.

🗒️Findr organizes information scattered across apps, links, and notes.

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

🥪BRIEF BITES

Former OpenAI Researcher Daniel Kokotajlo just published “AI 2027,” which forecasts how Superhuman AI will unfold over the next decade.

Anthropic’s Alignment Science Team (AST) discovered that Reasoning Engines like Claude 3.7 Sonnet don’t always say what they think.

Chinese Tech Giant ByteDance released “DreamActor-M1,” an AI Framework that turns static images of people into full-body animated videos.

OpenAI COO Brad Lightcap revealed that over 700 million AI-generated images were created within the first week of releasing 4o Image Generation.

💰FUNDING FRONTLINES

• Redpanda closes a $100M Series D for an Agentic AI Enterprise Platform.

• Hi Auto secures a $15M Series A to automate Drive-Thru Ordering with Conversational AI.

• Opsera raises a $20M Series B to scale an AI-Powered DevOps Platform for all apps, teams, and tools.

💼WHO’S HIRING?

• NVIDIA (Santa Clara, CA): Quantum Computing Software Intern, Summer 2025

• OptionMetrics (New York, NY): Jr. Model Validation Analyst, Entry-Level

• ION Group (New York, NY): Restructuring Data Analyst, Mid-Level

• ClassDojo (San Francisco, CA): Staff Analytics Engineer, Senior-Level

📒FINAL NOTE

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