Google Gemini’s Image Editing Gets Smarter Google upgraded Gemini’s image editing with sharper, more intuitive edits. The improvements keep Gemini competitive among the creative AI tools.
Nvidia’s Earnings: AI Boom Under Scrutiny Nvidia reported nearly $30B in quarterly earnings, holding an 88% market share in AI chips. It reinforces Nvidia’s central role in the AI boom and serves as a litmus test for the broader AI market.
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Sweden’s Farang Raises €1.5M for Next-Gen AI Models Stockholm startup Farang raised €1.5M seed funding to build agile, efficient large language models as a part of Europe’s growing AI research and innovation ecosystem.
Meta’s Superintelligence Lab Faces Early Turbulence Meta’s newly launched superintelligence lab is already showing cracks. Several top researchers have resigned over leadership struggles and lack of clear direction. The shakeup highlights the fragility of “moonshot” AI projects without strong vision.
⚖️ Policy, Ethics & Regulation
Regulators Warn AI Firms Over Child Safety A bipartisan coalition of 44 U.S. Attorneys General warned AI firms, including Meta, Google, OpenAI, and Apple, that they will face legal action if their platforms harm children. The pressure adds urgency for stricter child safety measures in AI platforms.
Research Reports
MIT report: 95% of generative AI pilots at companies are failing
MIT’s NANDA Initiative just released its State of AI in Business 2025 report and the findings are a wake-up call.
Only 5% of AI pilots drive rapid revenue growth.
The failure rate isn’t about bad models, it’s about misaligned adoption.
Most budgets go to sales/marketing AI, but the highest ROI is in back-office automation (cutting outsourcing, streamlining ops). While many enterprises overspend building “their own worse version,” smaller players are showing that you can build impactful apps at a fraction of the cost. (I recently shared how I built a content engine using Kimi AI at 1/10th the price of big-name models.) The data also shows:
Purchased AI tools succeed 2x more often than in-house builds.
Empowering line managers (not just central AI labs) drives adoption.
Only 5% of AI pilots drive rapid revenue growth.
The failure rate isn’t about bad models, it’s about misaligned adoption.
Most budgets go to sales/marketing AI, but the highest ROI is in back-office automation (cutting outsourcing, streamlining ops).
🔥 Conclusion Today’s updates show an industry balancing ambition with responsibility. Nvidia continues to dominate, while startups like Farang push new frontiers.
Regulators are sharpening their focus on safety, and sustainability remains a central challenge.
The takeaway?
AI’s next chapter won’t just be about performance...it will hinge on trust, ethics, and resilience.
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