🤖 What’s Going on With The AI Bubble?

🫧What’s Going on With The AI Bubble?

🕹️Fixing Overfitting With Game-Like Challenges

🛠Trending Tools

🥪Brief Bites

💰Funding Frontlines

💼Who’s Hiring?

The Dot-Com Bubble was driven by internet-based startups with limited track records and no clear paths to profitability. These internet-based startups were also heavily reliant on Venture Capital (VC) and Debt Financing (DF). Investors were driven by hype and speculation, focusing on metrics like “eyeballs” and “clicks.”

In comparison, The AI Bubble is largely driven by established Tech Giants like Microsoft, NVIDIA, and Meta with diversified revenue streams and substantial cash reserves. For example, Meta generates roughly $3.43 billion in Positive Free Cash Flow (FCF) per month as of early 2025. So, what does that even mean?

After paying all operating expenses (e.g., rent, salaries, and supplies) and making necessary long-term investments (e.g., data center construction and nuclear energy deals), Meta still has $3.43 billion left over every month.

The usage explosion of AI-powered products is insane. OpenAI just revealed that ChatGPT processes over 2.5 billion user queries (i.e., “prompts”) every day from around the globe. About 330 million of those are coming from the U.S. alone. That’s literally a single user query per American per day. ChatGPT has reportedly added over 4.5 million paying subscribers on Plus, Pro, Team, and Enterprise plans since the end of last year.

AI investments are a long-term play. AI’s potential use cases through drug discovery, humanoid robots, and self-driving cars will transform how the world operates. The global AI market is projected to soar from $189 billion in 2023 to $4.8 trillion by 2033, a 25-fold increase in just a decade.

AI Agents are like proactive digital assistants that can autonomously operate across websites to browse, book, or buy without us lifting a finger.

“ARC-AGI-3” aims to directly address overfitting, which occurs when AI Agents learn to memorize patterns rather than generalize knowledge.

Imagine teaching your dog to roll over, but only when you’re wearing a red shirt. He listens perfectly whenever you wear a red shirt, yet the moment you change into a blue shirt, he ignores you.

That’s overfitting: your dog learned to memorize patterns tied to your appearance (i.e., “red shirt = roll over!”) rather than generalize knowledge (i.e., “roll over whenever told!”).

“ARC-AGI-3” is an Interactive Reasoning Benchmark (IRB) that generates dynamic, game-like environments to rigorously test an AI Agent’s ability to learn, reason, and generalize in unfamiliar settings.

It’s not enough for an AI Agent designed to navigate digital storefronts to be able to browse products, compare prices, and complete purchases on a specific website under certain conditions.

It needs the ability to understand the general concepts of a “product,” “price,” and “purchase” so it can handle different digital storefronts across countless websites.

Context: I want to improve my money management skills,

Clarity: but I often struggle with sticking to my financial goals.

Guidance: Can you help me explore simple, actionable, and beginner-friendly strategies to manage {Insert Financial Scenario} so I can feel more in control of my finances?

Quandri raised a $12M Series A to scale AI automation for insurance agencies across North America.

Delve secured a $32M Series A to eliminate the annoying compliance busywork killing your momentum.

Radical AI closed a $55M Seed Round to pioneer the age of autonomous materials innovation.

Aircapture (Berkeley, CA): Data Engineering Intern, Fall 2025

NVIDIA (Westford, MA): Verification Engineer, CPU, Entry-Level

Meta (New York, NY): Software Engineer, Android, Mid-Level

OpenAI (San Francisco, CA): Sr. HW Test Engineer, Senior-Level