Tech • IA • Crypto
GameStop + eBay, Neural Computers, Elon vs OpenAI, Export Controls, Vibe Coded Projects
6/10TL;DR
A takeover bid by GameStop for eBay and the rise of AI models capable of replacing traditional software highlight a strategic turning point in tech and finance.
KEY POINTS
GameStop’s takeover bid for eBay
GameStop, led by Ryan Cohen, is offering to acquire eBay at $125 per share, a 46% premium. The offer combines 50% cash and 50% GameStop stock. The company has already built a 5% stake in eBay and may take the bid directly to shareholders if rejected.
A disputed financial structure
The deal’s credibility is questioned. With a market cap of about $11 billion and $9 billion in cash, GameStop falls well short of the $50–55 billion required. Even a reported $20 billion in bank backing would not close the gap, leaving uncertainty around the actual financing.
An ambitious strategic bet
Ryan Cohen aims to transform GameStop into a company worth over $100 billion. Acquiring eBay, a resilient platform despite rising competition, would reposition the legacy video game retailer in global e-commerce.
Strong fundamentals for eBay
Financial comparisons highlight the gap between the two firms. eBay generates about $50 billion in revenue, versus $15 billion for GameStop, with +8% growth compared to -5%. Its profitability is significantly higher, with an operating margin near 20%.
AI is reshaping software usage
Recent advances allow full financial analyses to be generated in a single query, in visual and directly usable formats. This drastically reduces the need for intermediary tools like spreadsheets or specialized software.
Toward “software 3.0”
The concept of “software 3.0”, popularized by Andrej Karpathy, describes a model where applications disappear in favor of direct interaction with AI models, which generate interfaces, analyses, or content on demand.
The possible end of certain applications
Many recently developed tools could become obsolete. Tasks that once required dedicated development can now be handled in a single interaction with a model, challenging the relevance of some startups.
Persistent limits in critical use cases
Despite progress, models remain unreliable in demanding areas like taxation. They struggle with complex documents and still require expert human oversight to avoid errors and hallucinations.
An emerging regulatory debate
In the United States, the executive branch is considering a framework to oversee AI models before deployment. The goal is to balance rapid innovation with risk mitigation in a sector already seen as strategic.
CONCLUSION
Between consolidation ambitions in e-commerce and the quiet revolution of AI, economic and technological balances are being reshaped, with major uncertainty around tomorrow’s dominant models.