Welcome back. Elon Musk's lawyers claim he "does not use a computer" in a legal filing against OpenAI—despite Musk posting on X about his "ancient PC laptop" and announcing "Just bought a new PC laptop" last year. Apparently when you own a social media platform, posting about your laptops doesn't count as computer usage.

In today’s newsletter:

• 🧑‍🏫 AI for Good: Teaching through play, powered by AI

• 🏀 AI is changing the way NBA teams evaluate talent

• ✏️ Anthropic wins key U.S. ruling in authors' copyright case

🧑‍🏫 AI for Good: Teaching through play, powered by AI

Psychologists are exploring how AI can enhance play-based learning by adapting to a learner's mood, behavior and progress in real time.

Early experiments show that AI companions can support vocabulary and comprehension by prompting curiosity during activities like reading, not by teaching directly, but by sustaining engagement in the learning process. Researchers believe this hybrid approach could support child development, motivation and emotional connection more effectively than static educational tools.

What happened: Researchers are developing the PLAY framework — Purpose, Love, Awareness and Yearning — to guide AI-supported learning systems. The framework emphasizes four principles that help create better learning environments across the lifespan, from early childhood to adulthood.

• Unlike one-size-fits-all systems, AI can detect when a learner is bored or frustrated and shift the experience to restore what psychologists call "flow state," when skill level matches challenge and attention is fully engaged.

• This makes AI especially promising for adaptive storytelling, gamified education and skill development. By observing patterns and behaviors, AI can personalize content, pace and interactions to support autonomy and creativity.

Why it matters: Play puts the brain in an optimal learning state. It encourages risk-taking, persistence and exploration without the pressure of judgment. Traditional educational tools struggle to maintain this state, but AI can help by adjusting task difficulty and offering feedback while keeping learners engaged.

Psychologists caution that not all AI support is helpful. If systems give answers too quickly or over-control learning environments, they may suppress curiosity. To preserve play's benefits, AI needs to offer guidance without removing the open-ended nature of exploration.

Try the CRM built to help small teams close big deals

Starter Suite is the easiest way for small businesses to get started with the world’s #1 CRM.

Designed for fast-growing teams, Starter helps you:

• Effortlessly create effective email campaigns with pre-built templates and actionable analytics.

• Speed up your sales process with guided deal management

• Deliver better service with built-in case resolution tools

• Make confident decisions with real-time dashboards

You don’t need IT support. You don’t need to install anything. And you don’t even need a credit card to try it.

Try it free for 30 days — and get 40% off when you’re ready to purchase.

👉 Start free trial

🏀 AI is changing the way NBA teams evaluate talent

NBA front offices are quietly reshaping how they scout, draft and develop players using AI. From analyzing how prospects speak in interviews to tracking muscle strain with medical imaging, teams integrate AI into every layer of player evaluation.

What began as a push for better stats has evolved into a full-scale tech shift with machine learning and language models playing a growing role in decision-making.

What happened: During interviews at the MIT Sloan Sports Analytics Conference, data scientist Sean Farrell presented a model to predict NBA success based on a player's language. Using 26,000 transcripts from 1,500 college athletes, his team trained a machine learning system to identify speech patterns linked to long-term performance.

• The model predicted NBA roster success with 63% accuracy using only language. With added context like stats and measurables, it reached 87% accuracy.

• Players who spoke in simple, present-focused terms were more likely to succeed. Words like "realize" and "believe" appeared more often among players who eventually made it. Complex sentence structure, surprisingly, correlated with lower success.

The Sixers use large language models to interpret years of scouting notes and tracking data. The Orlando Magic adopted AI platforms like AutoStats and SkillCorner to analyze player movement and decision-making.

Philadelphia president Daryl Morey compared AI input to adding another vote to the scouting process. Orlando assistant GM David Bencs said AI has made predictions "way more accurate."

Health data is also being treated with AI. Tools like Springbok Analytics turn MRI scans into 3D models that assess muscle quality and imbalance, already used by teams like the Jazz, Bulls and Pistons.

Why it matters: As teams seek the next edge, AI is shifting focus from stats alone to how players think, speak and move — opening new frontiers in measuring talent.

ACI.dev: MCP server for VibeOps — Go Beyond Vibe Coding, Let AI Deploy It Too

• ACI.dev’s VibeOps MCP can help you ship vibe-coded products to production.

• We let vibe coders go from idea → code → deploy → distribute, seemlessly.

• It’s as simple as adding a single MCP server to your Cursor.

• Automate your product deployment, let AI take your prototype to production.

Join the VibeOps waitlist now

Checkout the demo

• OpenAI quietly builds a Google Docs rival

• MrBeast used AI to create YouTube thumbnails. People weren’t pleased

• Here’s where AI data centers are popping up

• ElevenLabs launches its first mobile voice app

• DeepMind drops Gemini model for on-device robots

• Firefox is testing Perplexity as a built-in search engine

• Google defends AI overviews, says the web is doing just fine

• Abridge raises $300M to bring AI into healthcare conversations

• Oracle: Principal Product Manager- Healthcare AI

• Intel: Senior Director - AI SoC

• Roshi: Create custom, interactive learning material in a few clicks

• timeOS: An AI productivity companion that captures and summarizes the day, organizes information across tools and surfaces relevant knowledge

• Zing Data: Queries databases and creates shareable dashboards with natural‑language prompts

✏️ Anthropic wins key U.S. ruling in authors' copyright case

A federal court just issued the first major decision on how copyright law applies to generative AI. The verdict gave Anthropic a partial victory, affirming that using books to train its Claude model qualifies as fair use. However, it also exposed the company to possible damages regarding how those books were obtained and stored.

What the court found: U.S. District Judge William Alsup ruled that Anthropic's use of books without permission to train its artificial intelligence system was legal under U.S. copyright law, marking the first to address it in the context of generative AI.

• The judge said Anthropic made "fair use" of books by writers Andrea Bartz, Charles Graeber and Kirk Wallace Johnson to train Claude, describing the process as "quintessentially transformative."

• "Like any reader aspiring to be a writer, Anthropic's LLMs trained upon works not to race ahead and replicate or supplant them — but to turn a hard corner and create something different," Alsup said.

• Alsup said that Anthropic's copying and storing more than 7 million pirated books in a "central library" infringed copyrights and was not fair use.

The company will face trial in December, where damages could reach up to $150,000 per work if the infringement is ruled willful. That's $1.05 trillion for those doing mental gymnastics on 7 million pirated books.

How Anthropic built its dataset: Authors alleged that Anthropic used pirated versions from datasets including Books3, Library Genesis and Pirate Library Mirror.

• In January 2021, Anthropic cofounder Ben Mann "downloaded Books3, an online library of 196,640 books that he knew had been assembled from unauthorized copies," Alsup found.

• Mann then downloaded "at least five million copies from LibGen and another two million from PiLiMi", both known piracy sites.

• When Anthropic claimed the source was irrelevant to fair use, Alsup disagreed: "This order doubts that any accused infringer could ever meet its burden of explaining why downloading source copies from pirate sites that it could have purchased or otherwise accessed lawfully was itself reasonably necessary."

Anthropic later bought books in bulk and scanned them, but "That Anthropic later bought a copy of a book it earlier stole off the internet will not absolve it of liability for the theft," Alsup said.

The broader impact: This ruling comes as 39 copyright lawsuits against AI companies pile up in federal courts. The New York Times case against OpenAI and Meta's ongoing litigation suggests this ruling could have wide-reaching implications across the industry.

Judge Alsup has told AI companies that training on copyrighted works can be fair use when genuinely transformative, but pirating books isn’t. Companies will need legitimate data acquisition through licensing or public domain curation. This probably won’t kill innovation, but it will make it more expensive and methodical.

What's striking is Alsup's dissection of Anthropic's internal communications. The company's co-founder explicitly wanted to avoid the "legal/practice/business slog" of legitimate acquisition. 

By blessing training as fair use, Alsup told authors they can't prevent AI companies from learning from their work, only from stealing it. That's meaningful for copyright law, but cold comfort for writers worried about competition.

The real test comes in December's damages trial. Massive penalties would send a clear industry signal. Minimal damages might validate the "ask forgiveness, not permission" approach that has characterized AI development.

🤔 Your thought process:

Selected Image 1 (Left):

• “The Bridge looked plastic-y, and the shadow underneath it on the water looked very fake.”

• “That's not the SF skyline I know and love :)”

Selected Image 2 (Right):

• Ouch! And I live near the bridge, too! I should have figured any picture without Karl the Fog was a fake. :)

• “Wow. I was actually getting ready to type ‘too easy today.’”

💭 A poll before you go

The Deep View is written by Faris Kojok, Chris Bibey and The Deep View crew. Please reply with any feedback.

Thanks for reading today’s edition of The Deep View! We’ll see you in the next one.

P.S. Enjoyed reading? Take The Deep View with you on the go! We’ve got exclusive, in-depth interviews for you on The Deep View: Conversations podcast every Tuesday morning. Subscribe here!

P.P.S. If you want to get in front of an audience of 450,000+ developers, business leaders and tech enthusiasts, get in touch with us here.