What do people actually use AI voice mode for right now?

I love the idea of talking to AI, but I’m still waiting for a real agentic voice mode on the iPhone.

Siri AI is nice, but I don’t just want answers.

I want an assistant that can actually do things, manage tasks, make calls, negotiate, book stuff, and handle life admin while I just talk to it.

If the US government is already rationing access to Fable and GPT 5.6 class models, I’m genuinely worried.

What happens when true AGI arrives?

Do normal people actually get it, or do we only get the delayed, nerfed, “safe for public consumption” version while governments, labs and approved partners get the real thing?

AI was supposed to democratize intelligence.

It would be insanely dark if it just creates intelligence inequality on god mode.

I don’t think I’ll ever fully trust or use a model from Anthropic.

Not because Claude is bad, but because Anthropic is way too tied to the effective altruism / longtermist worldview.

That ideology already makes me nervous.

Combine it with AGI or ASI and it gets terrifying.

When people believe they are optimizing for “humanity’s future,” it becomes very easy to justify controlling, limiting, filtering, or deciding things for everyone else.

AGI should not be guided by a tiny group of people who think they know what is best for civilization.

This "Taste" Skill is cracked.

I can't believe I didn't discover it sooner - everyone should install this.

It works directly inside Claude Code, Codex, Hermes & more to completely kill AI-generated slop.

If you send this prompt to your agent, it will automatically install it

The Trump admin has asked OpenAI to stagger the release of GPT-5.6 over security concerns.

On Thursday, CEO Sam Altman told staff that the government will be approving access to GPT-5.6 customer by customer, a highly unusual approach.

Let this actually sink in:

The most powerful closed models on earth now require federal sign-off, one user at a time.

AI might've just hit its first real wall for progression.

Meanwhile, open-source models (like GLM-5.2 and
Sakana Fugu):

→ Can't be recalled
→ Can't be federally gated
→ Are already within months of frontier intelligence

This is the strongest bull case for open-source AI we've seen yet.

Seems like an easy win for China from here.

zenmux.ai

unsloth.ai/docs/models/glm-5.2

sakana.ai/fugu

Live footage of software engineers crawling to their laptops at 3 PM on Monday to send 1 prompt to Claude and let it do the rest of the week's work

New York Times: OpenAI is now leaning toward a 2027 IPO because the public market is testing whether AI giants deserve trillion-dollar prices before they prove durable profits.

IMO, SpaceX’s huge IPO and Anthropic’s confidential filing also change the OpenAI story because public-market capital is not infinite, and investors may already be digesting one massive AI-adjacent listing while preparing for another pure AI listing.

OpenAI cannot just ask for $1T in isolation, because every giant IPO competes for the same pool of institutional cash, risk appetite, and patience for loss-making growth stories.

So waiting until 2027 lets OpenAI avoid becoming the third huge test of AI-market depth in the same cycle

$MU Micron just reported a 15-fold profit jump because AI servers are now short of high-bandwidth memory, the stacked memory that keeps GPUs fed with data.

The shortage gives Micron rare pricing power, with adjusted gross margin reaching 84.9%, compared with 39% a year earlier.

DeepSeek is going on a hiring sprint, aiming to double every department.

The hiring spans AI core R&D, algorithms, deep learning research, full-stack development, and product roles, which means DeepSeek is no longer only tuning models but building the whole system around them.

I don't know how you feel inside, but i know a yacht would make you feel better

Mckinsey report - AI agents are quietly taking over the retail shopping cart and could mediate $3 Tn to $5 tn of global consumer commerce by 2030.

Instead of just suggesting a product, an AI agent can now scan multiple stores, check inventory, and build a ready-to-buy shopping cart.

This shift is happening across 6 different levels of automation.

- At the lowest level, the AI just compares prices and features so a human can make the final choice.

- At the highest level, your personal AI agent negotiates directly with a store's AI agent to get the best price and shipping terms.

Brands will increasingly compete to win over algorithms rather than just human shoppers.

For this to work, retail stores must make their product catalogs and return policies machine-readable by software via API

If a brand only focuses on looking good to humans but hides its inventory data, the AI agents will simply ignore it.

Stores that expose their pricing and stock data through clear software connections will dominate this new landscape, while those relying purely on flashy marketing will lose out as machines make the actual purchasing choices.

Automation ranges from simple product comparisons to full machine-to-machine negotiation.

Media and government: most of you can't afford to live so let’s increase inflation more

OpenAI & Anthropic: AI will replace you, but we can't afford our own compute

Apple & Microsoft: memory's expensive, will you join the permanent underclass?

New bear market headline:

According to the Financial Times, Binance will stop providing certain services for EU clients after failing to obtain a MiCA licence.

So Apple now charges $199 (+54%) for a nearly 4 year old streaming TV box and worst of all blamed memory prices?

This memory excuse only holds for its memory-heavy machines.

A couple GB of RAM doesn’t cost $70 more on a TV. They repriced an old device due to greed, not compute.

Looking back at the 2008 cycle, this identifies when every sector peaked.

What's interesting is "commodities" in the traditional sense already peaked in 2025 but the markets went higher. Trump attacking Iran that extended the cycle slightly by creating an inflation shock.

Since we're in the AI bubble, I would argue memory is the commodity this cycle that peaks after the market top. I'm already seeing signs DDR5 consumer pricing is rolling over.

The problem with memory boom and bust cycles is that when there's a shortage enterprises double or even triple order memory. The memory manufacturers have no idea which customers have double ordered.

When the memory cycle ends it's always the result of sudden rush of a cancelled orders due to falling prices or a sudden economic downturn.

Uh oh... CNBC just admitted AI demand is falling and that's why SpaceX, Anthropic and OpenAI are rushing to go public.

If CNBC is telling you this, the party is already over. 🚨

This is why GTA 6 didn’t release on PC first 😂

I wonder when GPT 6 actually gets released.

My guess is OpenAI won’t drop it until they have continual learning and real persistent memory figured out.

Because at some point, “just much smarter” isn’t enough anymore.

A genius with amnesia that can’t learn from experience is still weirdly limited.

⚠️In just 5 years, the world burned through nearly 300 YEARS of rare earth supply.

The clock on the metals that run modern life is moving faster than anyone admits.

This chart tracks how many years of supply life are left for key commodities, from 2020 to 2025.

Rare earth metals collapsed from 500 years of supply to just 218.

Lithium fell almost as hard, from 255 years to 128.
The battery metal halved its runway.

Uranium dropped from 121 years to 90, as nuclear demand quietly accelerates.

Even oil ticked down, from 61 years to 58.

The transition metals tell the real story.
Cobalt fell from 50 to 39.
The energy transition eats its own fuel.

The metals powering EVs, batteries, and AI are depleting fastest.

This is why critical minerals are becoming an investment story, not just an industrial one.

Scarcity is the trade of the next decade. The resources running out fastest are the ones the future needs most.

UBS says 60% of companies now watching AI budgets are moving to cheaper models and open-source Chinese models

The pressure is coming from extreme bills, including users spending up to $35K/month, teams exceeding quotas by 200%, and companies cutting internal AI tools from 5 to 2.

Companies are not abandoning AI, they are using model routing, which sends easy tasks to cheaper models and saves premium models for hard reasoning, code, and long-context work.

Chinese open-source models such as Qwen, DeepSeek, MiniMax, GLM, and Kimi now fit the enterprise cost curve because they can be run locally or used through cloud catalogs.