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- 📚 Authors win $1.5B from Anthropic
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Welcome, AI enthusiasts
Anthropic will pay at least $1.5 billion to settle claims from U.S. authors whose books were used to train its systems. The deal averages about $3,000 per work and could grow if more authors join. Let’s dive in!
In today’s insights:
Authors win $1.5B from Anthropic
Google pushes AI Mode
ChatGPT learns to admit uncertainty
Read time: 4 minutes
LATEST DEVELOPMENTS
ANTHROPIC
📚 Authors win $1.5B from Anthropic
Source: Anthropic
Evolving AI: Anthropic agrees to pay $1.5B in landmark copyright settlement with authors.
Key Points:
Authors set to receive about $3,000 per book, covering roughly 500,000 works.
Settlement includes destroying pirated files used for AI training.
Court approval pending, hearing scheduled for September 8.
Details:
Anthropic will pay at least $1.5 billion to settle claims from US authors whose books were allegedly used without permission to train AI systems. The payout, averaging $3,000 per work, could increase if more claims are filed. The deal requires Anthropic to delete pirated files, and it only covers past activity through August 25, 2025. Court approval is the next step before payments begin.
Why It Matters:
Paying $3,000 per book and deleting pirated files signals that AI teams need licensed, traceable datasets and provenance logs from day one or risk retroactive bills and forced deletions. Expect more publisher deals, tighter audits, bigger training budgets and, in some cases, retraining that slows release cadence and nudges pricing. Creators gain a payout path and stronger leverage in negotiations. If you roll out AI at work, ask vendors where the training data came from and whether they indemnify customers, or you might inherit the risk.
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GOOGLE
🔍 Google pushes AI Mode
Evolving AI: Google is preparing to make AI Mode the default search experience.
Key Points:
AI Mode expands on AI Overviews with chat-style follow ups.
Google says the open web is in "rapid decline" in its legal defense.
New AI Mode features let users buy tickets and book services directly.
Details:
Google’s AI Mode, already active in 180 countries, is edging closer to replacing traditional search as the default. It builds on AI Overviews by letting people continue conversations with the AI, turning search into a closed system. At the same time, Google’s lawyers are arguing in an antitrust case that the open web is shrinking, using this as a reason not to break up its ad tech business. The irony is that Google’s own shift to AI-driven search speeds up that very decline.
Why It Matters:
AI Mode keeps more of the journey inside Google: quick answers, restaurant bookings and soon tickets without leaving search. That trims referral traffic for publishers and squeezes comparison sites, shifting ad spend toward Google surfaces and away from the open web. Marketers should prep for fewer organic clicks, invest in structured data and first‑party lists, and test retail media and CTV mixes. Regulators face a search, ads and assistant stack merged into one.
Source: OpenAI
Evolving AI: OpenAI wants ChatGPT to say "I don't know" instead of guessing.
Key Points:
Language models will always make things up, but can improve at spotting uncertainty.
New benchmarks could reward models for honesty rather than risky guesses.
Early signs show ChatGPT declining to guess on tough math problems.
Details:
OpenAI says ChatGPT will always hallucinate, but the goal is to make it better at recognizing when it doesn’t know something. Instead of inventing answers, future models could pause, use external tools, or admit uncertainty. Current benchmarks push models to guess, which fuels false responses. By redesigning evaluations to accept “I don’t know,” OpenAI hopes to encourage more trustworthy answers.
Why It Matters:
Expect fewer bogus answers in support tickets, coding assistants, finance notes, and medical scribes, plus clearer audit trails for regulators. Early signs are visible already, from newer ChatGPT builds declining to guess to OpenAI’s IMO model refusing problem six. For buyers, ask for APIs that expose calibrated confidence and refusal rates, then track cost per avoided error, not just accuracy.
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