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Apple’s AI Gamble: Apple is reportedly flirting with the idea of letting Anthropic and OpenAI supercharge Siri. This bold move could finally transform Siri from a polite assistant into a true conversational powerhouse.

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Today’s AI Menu

▪️ Superintelligence labs, AI bands & Musk’s vertical play & more

▪️ Tutorial: How to use Humata.ai for chatting with your documents like ChatGPT?

▪️ 5 new AI tools to boost your productivity

▪️ AI Special Edition: A costly lesson for AI builders

▪️ AI Daily Prompt

TODAY IN WORLD OF AI

🚀Grok 4: Elon Musk’s next move in the AI arena

Big news for the chatbot wars: Elon Musk’s xAI is set to roll out Grok 4 right after July 4th. The upgraded version will run on xAI’s in-house “Gigafactory of Compute”, a bold attempt to tighten control over both AI model performance and hardware scale.

Why does this matter? For one, it signals Musk’s seriousness about turning Grok into more than just an edgy ChatGPT rival. He’s betting that deep vertical integration from chips to data to training will give xAI an edge over OpenAI and Anthropic. Unlike peers reliant on Nvidia or third-party compute, Musk wants to build and own the pipes too.

The kicker? Grok 4 will integrate directly into X (formerly Twitter). That means millions of real-time social posts could feed Grok’s learning loops fusing public conversation with AI augmentation at scale.

For founders and AI watchers, Grok 4 is a reminder: the future of chatbots won’t just hinge on model size. It’s about control of data, hardware, and distribution. If Musk’s “everything app” vision sticks, Grok might not just be another chatbot, it could become a real-time, AI-fueled knowledge network.

Keep your eyes on Grok’s rollout. How it performs will say a lot about whether vertical AI stacks are hype or the new frontier.

THE AI INSTITUTE

How to use Humata.ai for chatting with your documents like ChatGPT?

▪️ Visit humata.ai and sign up.

▪️ Upload your PDF document.

▪️ Ask questions in the chat (e.g., “Summarize this section” or “What are the key points?”).

▪️ The AI answers instantly in simple language.

▪️ Save, copy, or export responses.

FOOD FOR PRODUCTIVITY

5 tools for your productivity

🧑‍⚖️Spellbook: AI contract review assistant built directly into Microsoft Word.

🤖Lindy: Your AI executive assistant that handles scheduling, emails, and task automation.

📄Drafter AI: Build internal GPT-style tools for your business processes, no coding needed.

🎨Dream by Wombo: Create AI-generated artwork from simple text prompts in seconds.

🛠️Cogram: AI meeting assistant for engineers and analysts that generates action items and summaries.

Tool Video of the Day!

EVERYTHING ELSE YOU NEED TO KNOW

🧠Brainstorm: Meta is quietly ramping up its AI ambitions with a new ‘Superintelligence Lab.’ The goal? Build AI smart enough to rival or surpass anything out there.

🎧Groove: Over half a million Spotify users are vibing to a band that doesn’t even exist at least, not in the human sense. This AI-generated group is cranking out hits undetected, raising juicy questions: Are we dancing to code, and would we care if we knew?

📲Tailored: A new wave of AI-enabled personalization tools is changing how companies connect with us. From dynamic ads to custom content, brands are using ‘agentic AI’ to read our tastes like an open book.

🩺Diagnose: Microsoft’s AI system just beat real doctors at diagnosing complex health conditions. Researchers say it could help spot illnesses faster and cheaper than traditional clinics.

AI SPECIAL EDITION

🧩When computer vision fails: A hard lesson for AI builders

This deep-dive shows what can happen when a promising computer vision project drifts off course. A global retailer’s effort to track products on shelves using smart cameras and AI started strong until real-world complexity exposed its flaws.

Key pain points? First, the training data couldn’t handle endless variations in lighting, angles, and cluttered store shelves. The team underestimated the “hallucination” risk where the AI confidently guessed wrong, flagging out-of-stock items that were very much on the shelf.

Second, the hardware turned out to be as big a challenge as the models. Cameras failed in humid conditions, install costs ballooned, and integration with legacy systems proved brutal.

What’s the takeaway here? For founders and product leads, it’s a caution flag: AI pilots thrive in controlled labs but stumble in messy reality. Over-engineering the algorithm is tempting, but under-planning hardware constraints and edge cases can sink even the best model.

Before scaling your next AI dream, ask: What could go sideways in the real world? The lesson: stress-test assumptions, plan for edge cases, and keep your human fallback plan close. When vision works, it’s magic but when it hallucinates, trust erodes fast.

AI PROMPT OF THE DAY

Prompt for generating a market comps summary for IPO analysis

Prompt: Generate a market comps summary to support an IPO analysis. Include comparable companies’ key metrics like market capitalization, revenue, EBITDA, P/E ratio, EV/EBITDA, and growth rates. Present a side-by-side comparison that highlights valuation multiples, industry benchmarks, and any notable differences. Summarize insights to help assess whether the IPO is fairly valued, undervalued, or overvalued relative to its peers.

Helpful? Check out our best AI prompts!

Thanks for reading.

Until tomorrow!

Shinky & the Hanoomaan AI team