Good morning, AI enthusiasts. The AI reasoning revolution just got a lot more affordable — with Google launching its new Gemini 2.5 Flash in preview with performance rivaling top models at significantly lower costs.

With a toggle to control when thinking kicks in and a “budget” for balancing quality, speed, and cost, could this be the model that finally scales reasoning to the masses?

P.S. — our next workshop is TODAY at 4 PM EST. Learn how to unlock the full potential of o3, o4-mini, and GPT-4.1 and build with OpenAI’s newest models. RSVP here.

In today’s AI rundown:

• Google’s Gemini 2.5 Flash with ‘thinking budget’

• Profluent finds scaling laws for protein‑design AI

• Transform your spreadsheets with AI in Google Sheets

• Meta’s FAIR shares new AI perception research

• 4 new AI tools & 4 job opportunities

LATEST DEVELOPMENTS

GOOGLE

🤔 Google’s Gemini 2.5 Flash with ‘thinking budget’

Image source: Google

The Rundown: Google just launched Gemini 2.5 Flash — a hybrid reasoning AI in preview that matches o4-mini, outperforms Claude 3.5 Sonnet on reasoning/STEM benchmarks, and introduces a new ‘thinking budget’ to optimize cost vs. quality.

The details:

• 2.5 Flash shows significant reasoning boosts over its predecessor (2.0 Flash), with a controllable thinking process to toggle the feature on or off.

• The model shows strong performance across reasoning, STEM, and visual reasoning benchmarks, despite coming in at a fraction of the cost of rivals.

• Developers can also set a “thinking budget” (up to 24k tokens), which fine-tunes the balance between response quality, cost, and speed.

• It is available via API through Google AI Studio and Vertex AI, and is also appearing as an experimental option within the Gemini app.

Why it matters: OpenAI may have dominated the conversation this week, but Google is shipping right alongside them. The controllable, budgeted reasoning is an interesting customization, with users able to hit the feature only when a task needs it — unlocking affordable, high‑volume use cases and saving thinking for more complex jobs.

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COMPANY

🧬 Profluent finds scaling laws for protein‑design AI

Image source: Profluent

The Rundown: Profluent announced ProGen3, a new family of AI models that can design complex proteins from scratch — with the results marking the first evidence of AI scaling laws in biology, proving larger models and more data create stronger results.

The details:

• The Biotech company's 46B model was trained on 3.4B protein sequences, surpassing previous datasets and showing improved protein generation.

• It successfully designed new antibodies matching approved therapeutics in performance, yet distinct enough to avoid patent conflicts.

• The platform also created gene editing proteins less than half the size of CRISPR-Cas9, potentially enabling new delivery methods for gene therapy.

• Profluent is making 20 "OpenAntibodies" available through royalty-free or upfront licensing, targeting diseases that affect 7M patients.

Why it matters: If scaling trends hold, Profluent’s approach could turn drug and gene‑editor design from years‑long lab work into a faster, more predictable engineering problem — rewriting how new therapies are discovered. These trends also suggest we're just at the beginning of AI's impact on drug discovery and medicine.

AI TRAINING

🔢 Transform your spreadsheets with AI in Google Sheets

The Rundown: In this tutorial, you will learn how to use Google Sheets' new AI formula to generate content, analyze data, and create custom outputs directly in your spreadsheet—all with a simple command.

Step-by-step:

1. Open Google Sheets through your Google Workspace account (it’s slowly being rolled out).

2. In any cell, type =AI("your prompt", [optional cell reference]) with specific prompts like "Summarize this customer feedback in three bullet points."

3. Apply your formula to multiple cells by dragging the corner handle down an entire column for batch processing.

4. Combine with standard functions like IF() and CONCATENATE() to create powerful workflows, and use "Refresh and insert" anytime you need updated content.

Pro tip: You can also include formatting instructions directly in your prompt, such as "in table format" or "as a numbered list," to control how your output appears in the cell.

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META

🔬 Meta’s FAIR shares new AI perception research

Image source: Meta FAIR

The Rundown: Meta’s FAIR research arm just published five new open-source AI research projects focused on perception and reasoning, showcasing advances in computer vision, 3D understanding, and collaborative AI capabilities.

The details:

• Perception Encoder shows SOTA performance in visual understanding, excelling at tasks like ID’ing camouflaged animals or tracking movements.

• Meta also introduced the open-source Meta Perception Language Model (PLM) and a PLM-VideoBench benchmark, focusing on video understanding.

• Locate 3D enables precise object understanding for AI, with Meta publishing a dataset of 130,000 spatial language annotations for training.

• Finally, a new Collaborative Reasoner framework tests how well AI systems work together, showing nearly 30% better performance vs. working alone.

Why it matters: This research batch focuses on AI building blocks like perception, 3D understanding, and reasoning — key steps toward more capable embodied agents and machine intelligence. We’re officially crossing into new territory, with systems that can finally understand and interact with the physical world in advanced ways.

QUICK HITS

🛠️ Trending AI Tools

• 🎯 Gamma 2.0 – Easily craft stunning AI presentations, interactive websites, social carousels and more from simple text prompts*

• 🧠 o3 and o4-mini - OpenAI’s new models with visual reasoning and tool use

• ⚙️ Codex CLI - OpenAI’s open-source coding agent for users’ terminals

• 🖥️ Copilot Computer Use - Build agents that can use and navigate GUIs

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💼 AI Job Opportunities

• 🧠 Deepmind - Strategy & Operations Principal

• 📝 Meta - Content Strategist

• 📱 OpenAI - iOS Engineer

• 💰 Harvey - Sr. Compensation Analyst

📰 Everything else in AI today

OpenAI’s new o3 model scored a 136 (116 offline) on the Mensa Norway IQ test, surpassing Gemini 2.5 Pro for the highest score recorded.

UC Berkeley’s Chatbot Arena AI model testing platform is officially breaking out from its research project status into its own company called LMArena.

Perplexity reached a deal with Motorola and is reportedly in talks with Samsung to integrate its AI search platform into their phones as the default assistant or an app.

xAI’s Grok rolled out memory capabilities for remembering past conversations, also introducing a new Workspaces tab for organizing files and conversations.

Alibaba released Wan 2.1-FLF2V-14B, an open-source model that allows users to upload the first and last frame image inputs for a coherent, high-quality output.

Music streaming service Deezer reported that over 20K AI-generated songs are being published daily, with the company using AI to filter out the content.

OpenAI reportedly explored acquiring Cursor creator Anysphere before entering the current $3B discussions with rival Windsurf for its agentic coding platform.

COMMUNITY

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Join our next workshop today at 4 PM EST with Dr. Alvaro Cintas, The Rundown’s AI professor. By the end of the workshop, you’ll be ready to start building with OpenAI’s latest models — o3, o4-mini, and GPT-4.1.

RSVP here. Not a member? Join The Rundown University on a 14-day free trial.

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See you soon,

Rowan, Joey, Zach, Alvaro, and Jason—The Rundown’s editorial team