AI Money Keeps Flowing as Deepseek Plans Record Raise and Core Automation Quadruples Valuation in Weeks

Why It Matters

The massive capital inflows signal investor belief that scalable, revenue‑generating AI platforms will dominate the next tech wave, while rapid valuation jumps highlight the market’s appetite for novel AI research models.

Key Takeaways

• Deepseek aims to raise up to ¥50 bn ($7.35 bn) in new funding.
• Founder Liang Wenfeng may fund 40% of Deepseek round himself.
• Deepseek valuation could exceed $51.5 bn after the raise.
• Core Automation targets $4 bn valuation after $100 m Series A.
• Core Automation develops AI models that continue learning post‑training.

Pulse Analysis

The AI funding boom shows no signs of slowing, with Deepseek’s planned ¥50 billion ($7.35 billion) raise marking the largest ever for a Chinese AI firm. This infusion not only reflects the global appetite for advanced language models but also underscores China’s strategic push to compete with Western giants. By potentially pushing Deepseek’s market cap above $51.5 billion, the round could reshape the competitive hierarchy, attracting more talent and accelerating research pipelines in a market traditionally dominated by a handful of players.

Beyond the capital, Deepseek is gearing up for a commercial push with the upcoming DeepSeek V4.1 release slated for June. The upgrade promises richer enterprise tools, enhanced multi‑modal capabilities, and stronger image‑and‑audio processing, aiming to translate research breakthroughs into billable services. Investor concerns over revenue gaps and talent drain to rivals like Xiaomi and ByteDance are being addressed through these product enhancements, positioning Deepseek to capture a slice of the burgeoning AI‑as‑a‑service market and generate sustainable cash flow.

Core Automation’s meteoric rise illustrates how quickly valuation can accelerate when a startup promises a new learning paradigm. Founded by ex‑OpenAI researcher Jerry Tworek, the company secured $100 million at a $1 billion valuation and is now courting a $4 billion figure within weeks. Its focus on AI models that keep learning after deployment could lower the cost of model updates and open new enterprise use cases, challenging incumbents that rely on static training cycles. If successful, Core Automation may set a new benchmark for post‑training adaptability, prompting both investors and competitors to prioritize continuous‑learning architectures in the next wave of AI innovation.