🤖 The $11.5 Billion Hook Cast Across Wall Street

🎣 The $11.5 Billion Hook Cast Across Wall Street

🚑 AI Beats Doctors at Correctly Diagnosing Patients

📍 6 AI Stock Sectors

🛠️ 5 Trending Tools

🥪 4 Brief Bites

💰 3 Funding Frontlines

💼 4 Job Opportunities

Anthropic announced the formation of a new AI services company valued at $1.5 billion, partnering with Blackstone, Hellman & Friedman, and Goldman Sachs to fund the integration of Claude across mid-sized portfolio companies like community banks and regional health systems.

OpenAI reportedly launched a new investment vehicle valued at $10 billion, nicknamed “DeployCo,” partnering with global PE firms, including TPG, Bain Capital, and Brookfield Asset Management, to access a large network of portfolio companies across every industry imaginable, ranging from Viking Cruises to Athenahealth.

OpenAI reportedly offered these global PE firms a guaranteed minimum annual return of 17.5% over the next five years on the capital they commit, acting as an aggressive fiscal incentive to secure these strategic partners, especially since Anthropic currently maintains a lead when it comes to capturing business customers.

In the normal business world, if you invest in a company and it fails, you lose your money. OpenAI effectively guaranteed returns for investors. If “DeployCo” only makes 10% profit, OpenAI will dip into its own pocket and pay the extra 7.5% for the global PE firms to reach the minimum guaranteed annual return of 17.5%. It’s a calculated risk that suggests OpenAI might be eyeing an IPO window that falls within late 2026 or early 2027.

Today, Anthropic’s run-rate revenue is $30 billion, representing over a tenfold increase in revenue each year for the past three years. For context, Anthropic projects $70 billion in annual revenue by 2028, with business customers accounting for nearly 80% of that annual revenue. The AI services company is set to continue aggressively expanding enterprise AI efforts.

HMS recently revealed that “OpenAI o1-preview,” a reasoning model released on Sept. 12th, 2024, outperformed a pair of experienced attending physicians at diagnosing 76 real-world emergency room cases. It provided higher-quality “differential diagnoses”: a list of possible conditions that could be causing the symptoms.

The reasoning model excelled at the initial ER Triage stage, when patients are first admitted and there’s very little diagnostic data available. At this initial stage, it correctly identified the “exact or very close diagnosis” 67.1% of the time, compared to 55.3% and 50.0% for the pair of experienced attending physicians.

Even crazier, the certified medical evaluators tasked with judging the quality of each diagnosis were “almost entirely unable” to tell which diagnostic conclusions were suggested by the reasoning model or the pair of experienced attending physicians. For reference, they correctly identified the source only 15.2% of the time.

In some of medicine’s toughest clinical cases, the hardest part isn’t choosing the right diagnosis; it’s that initial step of thinking of it at all. According to the AMA, roughly 81% of healthcare professionals now ask AI for help in medical practice.

In healthcare, almost 75% of diagnostic errors are rooted in cognitive factors like overconfidence, premature closure, and availability bias. AI acts as a “cognitive safety net.” In simple terms, it doesn’t replace the doctor’s brain; it balances its natural biological weaknesses.

definity raised a $12M Series A to scale agentic data engineering.

Featherless closed a $20M Series A to power open-source AI projects.

JuliaHub landed a $65M Series B to simulate complex physical systems.

Tesla (Palo Alto, CA): AI Performance Engineer Intern, Summer 2026

NVIDIA (Santa Clara, CA): Datacenter GPU Power Architect, Entry-Level

Anthropic (Seattle, WA): Accounts Receivable Specialist, Mid-Level

OpenAI (London, UK): ChatGPT Infra. Engineer Manager, Senior-Level