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Latest in AI…

Motorola is turning its phones into answer engines with help from Perplexity

The story in simple terms:

Motorola is turning its phones into answer engines—with help from Perplexity

Perplexity AI just made its biggest distribution move yet.

It’s partnering with Motorola to bring its AI search engine directly into smartphones making it native, not just an app.

Here’s everything you need to know about:

The integration makes Motorola the first smartphone brand to embed Perplexity’s AI directly into its devices

Perplexity joins Moto AI alongside Copilot, Gemini, and Meta for handling voice queries and complex questions

Users will get 3 months free of Perplexity Pro, including Deep Research, to test out its assistant-like capabilities

The goal: shift from search engines full of links to direct, conversational answers—in your pocket

CEO Aravind Srinivas says it’s not about revenue—it’s about usage and habit-building Native placement increases visibility and reach, especially on weekends when users typically don’t engage with AI

The move follows a wave of AI hardware experiments (Humane, Rabbit) that mostly flopped—but this one skips hardware risk

Here’s what we think:

This isn’t just about adding a new AI feature, it’s about reshaping where and how we use AI. Embedding answer engines into the operating layer of phones could be the wedge that makes AI invisible, habitual, and ever-present. The question now isn’t can AI replace search—it’s when.

Anthropic sets 2027 deadline to decode AI’s black box

The story in simple terms:

Anthropic’s CEO just issued a wake-up call.

In a new essay, Dario Amodei argues that the tech industry is racing ahead with AI capabilities without understanding what’s really going on inside the models.

Here’s what we know so far:

Amodei says it’s “basically unacceptable” to deploy powerful AI without reliable interpretability tools

Anthropic’s new goal: detect and diagnose most major AI issues by 2027

He compares AGI to “a country of geniuses in a data center” that we don’t understand or control

The company is pioneering “mechanistic interpretability”—like doing MRIs on AI brains to trace how decisions are made

So far, they’ve identified a few model circuits (like U.S. city-state associations) but believe there are millions more

Amodei is calling on OpenAI, DeepMind, and governments to prioritize transparency and require disclosure of safety practices

He argues interpretability won’t just improve safety it could offer a long-term commercial edge

Here’s what we think:

We’ve spent years building intelligence without understanding it. This essay marks a clear line in the sand. Amodei’s not saying “pause” he’s saying “get serious.” AI that we don’t understand isn’t just risky it’s irresponsible. Interpretability won’t slow us down. It’s what will make the next phase of progress safe, stable, and real.

Off-the-shelf AI is failing teams. Here’s how to make it work like one.

The story in simple terms:

A Fortune 500 retailer gave its contract team an AI tool.

It was smart, fast—and mostly useless.

Why? It didn’t know how the team actually worked.

What you need to know:

• Most AI tools fail because they’re too generic—trained broadly, but blind to local workflows

• Real productivity comes when AI tools are customized to reflect how teams actually get work done

• The solution? “Work graphs” that map team behavior, and “reverse mechanistic localization” (RML) to train models on that context

• RML flips the script: instead of teaching AI how to think, you teach it how your people work

• At the retailer, once the AI was fine-tuned with team-specific data, contract output improved by 30% and manual edits dropped by half

• Crucially, this isn’t one-and-done—it’s a feedback loop. Teams provide new context, and the model keeps learning

• Done right, this turns AI from a novelty into a high-performing teammate that knows your systems, habits, and priorities

Here’s what we think:

Every company is racing to adopt AI. But if you don’t ground that AI in how your team actually operates, you’re buying a brain without a body. The winners won’t be the ones with the most powerful models. They’ll be the ones who make those models feel like part of the team.

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