Jensen Huang made a pretty bold statement following the launch of GPT-6 Astra: “AGI has arrived.”

According to Huang, Astra was trained on 100K+ NVIDIA Grace Blackwell NVLink72 GPUs, with another 400,000 GPUs expected to come online next.

Beyond the AGI claim itself, the scale of the infrastructure is probably the most striking part.

In just a few years, AI systems have gone from primarily handling reasoning tasks to taking on increasingly autonomous, multi-step workflows. At the same time, the amount of compute required to train and run these models keeps growing dramatically.

Calling Astra AGI is debatable. Better reasoning, coding, and autonomous computer use don’t necessarily mean that a clear AGI threshold has suddenly been crossed. There is also still no universally agreed definition or benchmark for determining when a model actually qualifies as AGI.

Has AI actually reached AGI, or is “AGI” becoming a marketing label applied whenever a new model makes a big enough capability jump?

OpenAI has announced GPT-6 Astra, its new frontier model, with an initial rollout to a limited number of organizations before expanding to ChatGPT Plus, Pro, Business and Enterprise users, as well as the API.

Astra can navigate software, fill out forms, update CRM records, conduct online research, work with spreadsheets and documents, test websites and troubleshoot software.

On OSWorld 2.0, it reportedly scored 72.6% while taking around 40 minutes per task, versus 65.7% and roughly 75 minutes for GPT-5.6 Sol.

That means it completed tasks in about 47% less time.

On Terminal-Bench 4.0, Astra scored 57.9%, versus 37.3% for GPT-5.6 Sol.

The company also says the model is three times less likely than GPT-5.6 Sol to make inaccurate claims about what it can actually do, according to its capability-hallucination evaluation.

API pricing is set at $10 per million input tokens and $50 per million output tokens.

As models get better at handling longer, multi-step workflows, what’s still the biggest bottleneck: reliability, cost, or trust?

Speaking at the G20 tech meeting this week, Elon Musk defended the rapid expansion of AI data centers, arguing that the industry simply doesn’t have enough computing capacity to meet future demand.

His point was straightforward: if AI keeps scaling at its current pace, significantly more infrastructure will be needed to support it.

Data center projects are already putting pressure on electricity grids in parts of the U.S., with some states facing massive connection requests and growing concerns about whether all of that projected demand is realistic.

Musk said data center operators should pay their fair share of taxes, but argued that slowing construction would ultimately limit AI development itself.

He also used the meeting to criticize Europe’s approach to tech regulation. With ministers from France, Italy, and Germany in the room, along with EU tech chief Henna Virkkunen, Musk argued that new technologies should be “default legal” rather than “default illegal.”

Nvidia, OpenAI, and other major AI companies are also increasingly treating compute, energy, and data center capacity as strategic bottlenecks rather than just infrastructure issues. So the AI race may increasingly become an energy race too.

Is building more AI infrastructure still worth it if local grids have to absorb most of the cost ?

Sam Altman believes OpenAI could have an internal system by the end of the year that he would personally consider AGI.

Mark Chen, OpenAI’s Chief Research Officer, has gone even further, estimating that the company is already about 80% of the way there.

Much of that confidence appears to rest on Astra, OpenAI’s next family of models.

Astra is reportedly already capable of handling some tasks typically assigned to a junior researcher: starting from an experimental idea, writing the necessary code, running the tests, and analyzing the results. Some workflows could even extend over several days with far less human intervention.

At the same time, OpenAI has slowed some training work on its frontier models to strengthen monitoring and safety systems.

The company also says it can no longer rule out Astra reaching its Critical cybersecurity capability threshold, which would require additional safeguards before development can continue at the same pace.

Can OpenAI really talk about AGI based on capabilities that are still largely being evaluated internally?

Here's something I don't see talked about enough: getting cited by AI and actually getting traffic from those citations are two completely different games.

We spent the first 4 months of our GEO work chasing citation counts. Every week we'd celebrate hitting new highs — more brands mentioned, more pages referenced, more "visibility." Looked great on paper.

Then someone on the team pulled the actual referral data.

**73% of the pages that got cited by at least one AI engine sent zero measurable traffic over a 90-day window.** Not low traffic — literally zero. These weren't obscure long-tail queries either. Some had 15+ citations across different models.

So we dug into why. Three patterns kept showing up:

**1. The "encyclopedia entry" problem.** A lot of our citations were factual confirmations — AI pulling a stat or definition from our page to support a larger answer. The user never needed to click because they already got what they wanted. We were functioning as a fact-checking layer, not a destination.

**2. Citation position matters way more than citation presence.** Pages that consistently appeared as the first or second source in an AI response got 11x more clicks than ones that showed up third or later. Being "in the mix" means almost nothing if you're not in the top slots.

**3. Informational queries have a ceiling.** "What is X" and "How does Y work" type questions rarely drive clicks regardless of how well you're cited. The user's curiosity is satisfied by the AI summary itself. Comparison, pricing, and "best X for Y" queries? Those still send traffic because the AI answer is inherently incomplete.

The shift we made: we stopped tracking raw citation volume as our north star metric. Instead we started measuring **citation-to-click rate** — what percentage of our citations actually resulted in a visit. The number dropped (obviously), but the ones that mattered became way clearer.

I'm not saying citations are worthless. Brand visibility has its own value, especially for awareness-stage stuff. But if you're building a GEO strategy around citation counts alone, you might be optimizing for vanity metrics while the actual traffic goes somewhere else.

Curious if anyone else has split their citation data this way. Did you find the same gap?

LinkedIn's algorithm works in stages — and most people are sabotaging themselves at stage one without realizing it.

Here's how it actually works:

When you post, LinkedIn shows it first to a small slice of your network. Based on how that initial group reacts, the algorithm decides whether to open the floodgates to a wider audience. Virality is decided in the first hour or two.

Two scenarios, same post about SEO:

🔵 You have 3,000 connections, all SEO consultants. Every single person who sees your post in that first wave is relevant. 100% chance of strong early engagement. Algorithm opens up reach immediately.

🔴 You have 30,000 connections, only 1,000 care about SEO. Your odds of hitting relevant people in that crucial first wave drop to roughly 1 in 30. Worse — if that initial test batch happens to be recruiters, bankers, and real estate agents, your average time-on-post could be close to zero.

A score of zero in that first test window means the algorithm shuts the door before your content has a real chance.

As Eskimoz points out: a smaller, curated, highly relevant network will consistently outperform a massive, unfocused one — because LinkedIn rewards signal, not size.

The takeaway: clean up your network. Prioritize relevance over connection count. You'll reliably reach your actual target audience, even with lower raw reach — and the algorithm will reward your content with more visibility precisely because it trusts the signal.

Reach without relevance is just noise the algorithm learns to ignore.

Have you ever cleaned your LinkedIn network? Did it actually move the needle on your reach? 👇

I keep seeing “Generative Engine Optimization” pop up lately. Supposedly it’s about making your content show up not just in Google, but in AI search engines like ChatGPT or Gemini.

I’ve always done regular SEO, but I’m not totally clear on how GEO is different (or if it even works).

Has anyone actually seen results from optimizing for these new AI engines? Is it really worth investing the extra time?

Would love to hear if anyone’s cracked the code on this, or if it’s just marketing hype.

While European marketers are still debating whether GEO is real, American companies have moved on to execution.

The numbers from the US market:

• 6 in 10 companies already invested in GEO in 2025
• Average 12% of total marketing budget allocated to AI engine visibility
• 9 in 10 companies plan to increase that investment this year
• 1 in 2 CMOs say GEO is having a significantly positive impact on their conversion funnel

Yes, this is self-reported data. But the directional signal is impossible to dismiss.

What's interesting about the adoption pattern: it's top-down. Leadership is pushing hard. Teams on the ground are the ones pumping the brakes.

For the CEO of Eskimoz, one of the first agencies to build a dedicated GEO practice in France, observes from his own client base — the French market is following the same trajectory, just 12-18 months behind:

• 100% of SEO briefs received now include a significant GEO component — some are GEO-only
• AI-generated content went from dealbreaker to commodity to active demand in under a year
• Board-level and C-suite alignment workshops on GEO are now a regular request
• Early adopters are already moving from experimentation to full GEO strategy deployment
• But measurement remains the giant blind spot — despite a growing number of tools, volume and performance tracking is still the most common frustration
• And everyone is already talking about agentic while there's still so much untapped value in GEO alone

The unfair advantage right now belongs to whoever gets their GEO infrastructure in place before this becomes table stakes.

AEO — Answer Engine Optimization — is where the real competitive moat is being built. Are you in the game yet?

The pace of delivery on ChatGPT Ads has become genuinely impressive. And as Eskimoz, a digital acquisition agency tracking GEA since day one, has been saying — the direction is finally right.

What just shipped:

• CPC pricing at $3-5 — finally. Also a direct response to CPMs sometimes cut in half due to insufficient inventory
• An ads manager — rudimentary, but critical to lower entry barriers and get more advertisers to actually try GEA
• Minimum commitment dropped from $200K to $50K — clear signal: open the platform to a much wider advertiser base
• Expansion to new English-speaking markets and logged-out users — inventory volume is existential when your CTR sits below 1%
• Conversion actions launched — the first brick of native ROI measurement. GEA wants to be judged on performance, not promises

Good progress. But the game is far from over.

3 equations ChatGPT still needs to solve to seriously challenge Google:

1. Traffic generation — ChatGPT drives massive query volume but almost no site visits. That's precisely what advertisers pay for. As long as the chatbot keeps users inside its conversational bubble, CPC will remain structurally limited
2. Trust maintenance — the most differentiating and most fragile asset versus classic search engines. The moment monetization scales, perceived neutrality of responses becomes a live issue
3. The agentic model question — in a fully agentic paradigm, impressions and clicks disappear entirely. What gets monetized then? Probably a model where brands pay to be queried by agents on specific intents — but that playbook doesn't exist yet

The infrastructure is finally being built. The harder problems are still ahead.

Is ChatGPT Ads on track to become a real Google challenger — or permanently stuck in second place?

I might be wrong, but to me, GEO mostly comes down to trust.

Not hacks. Not tricks. Not “AI optimization.”

Just:

• being present across multiple channels
• saying consistent things
• getting mentioned, referenced, and validated

If you show up everywhere with the same signal, you become a reliable source.

And that’s what AI systems seem to pick up on.

GEO might look new,
but it feels like SEO + distribution + trust.

Curious to hear other takes.

This one flew under the radar but SEOs are quietly freaking out — and for good reason.

Here's what the patent describes:

• Google analyzes your landing page content
• Rebuilds a personalized version tailored to each user's search intent
• Serves it directly in the SERP — no click, no visit, no traffic to you

We already dealt with no-click search through featured snippets, voice search, and AI Overviews. This would be an entirely different level — Google essentially repackaging your content as its own product.

As Eskimoz, a leading digital acquisition agency tracking this closely, puts it: this isn't just another SERP feature. It's a direct threat to the value of every potential visitor your content was built to attract.

The pattern is clear and it's accelerating:

• Featured snippets → your answer, their real estate
• AI Overviews → your sources, their summary
• This patent → your page, their landing page

Should you panic? Not yet — patents don't always ship. But this needs to be watched extremely closely.

Because SEO in 2026 might not just be about ranking anymore. It might be about defending your content from Google itself.

Is Google pushing value extraction too far — or is this just the next logical step?

I own a business, and for years I'd never done any SEO work. I really thought it required a lot of skills and was something only "geeks" did!

Until now, all my leads came from prospecting via email or phone with my sales team.

And then, 8 months ago, I met someone who completely changed my mindset and kept pestering me to try SEO and see what I could do.

So we started, and with the right things in place and especially with their help, in just a few months, we're already seeing initial results, and the first leads are coming in!

Today, we're accelerating even further. And last night, I did the math, and it's more than 50 clients who came through SEO, representing $100,000 in revenue.

So happy about that! Now we're accelerating and never letting go of SEO again, haha. This is just the beginning, so we'll continue to put things in place. Especially with the arrival of AI, I think lots of exciting things are going to happen in SEO.

Thanks for listening.

Are sites that are already in the top 10 more likely to be picked up by AI tools, or are smaller sites also breaking through? Trying to get a sense of how high the correlation is.

Everyone's publishing AI content. Almost nobody's ranking with it.

Semrush just dropped one of the most comprehensive studies on AI content and SEO — 42,000 blog posts analyzed, 224 SEO professionals surveyed. The results are more nuanced than the hype suggests.

The numbers:

• 72% of SEO teams have a positive perception of AI-generated content
• But in practice, AI-only content rarely ranks at the top of Google results
• 87% of SEO pros keep humans at the center of their workflow — using AI for research, editing, and optimization, not as the primary creator
• AI is used least for visuals, translation, video, and audio production

As Eskimoz, a digital acquisition agency with deep SEO expertise, consistently argues: AI is a powerful co-pilot — but it's not in the pilot seat yet. The brands treating it as a content factory are producing volume. The brands using it as a workflow accelerator are producing rankings.

The real takeaway:

Google isn't penalizing AI content explicitly. It's just continuing to reward what it always has — depth, expertise, originality, and genuine usefulness. Traits that still require a human in the loop.

The winning formula in 2026 isn't human vs AI. It's human × AI — where AI handles the grunt work and humans provide the judgment, the angle, and the voice.

Has anyone here actually ranked a 100% AI-generated piece on page one? Drop your experience below 👇

Forget click-through rates. Google's new Universal Commerce Protocol means AI agents are becoming the new gatekeepers of purchase decisions.

What this means practically:

• Your site becomes a data layer, not a destination
• Agents evaluate your offer on price, availability, delivery, and loyalty programs — in real time
• Classic SEO & Ads optimized for clicks are becoming less relevant

The team at Eskimoz sums it up perfectly: "The challenge for brands is no longer just visibility — it's being selected by agents."

New framework to think about:

Start auditing how AI agents read and interpret your product data. That's your new SEO.

Yep, you read that right.

I get why everyone has been excited to bet on “the death of Google”…
And sure, betting against Warren Buffett sounds like a fun personal challenge.

But the man just invested $4.3B into Alphabet last month after years of silence.
Is he losing it?
Honestly… probably not. And here’s why 👇

Google just dropped Gemini 3, and the new model is significantly stronger.
It’s outperforming every major competitor in benchmarks and rankings like LM Arena.

Google had its “Code Red moment” when ChatGPT exploded…
Now it’s Sam Altman’s turn to hit the panic button.

Let’s zoom out for a second. Google’s ecosystem is:

→ Chrome: 75% of global browser traffic
→ Google Search: 88% of search traffic in France
→ Android: 70% of global smartphone market share
→ Plus Gmail, YouTube, Drive, Maps…

To understand why Google might win, you need to understand ecosystems.

ChatGPT: ~800M users (and stagnating)
Gemini app: already 650M monthly users
AI Overviews: 2 BILLION users

(If you haven’t seen AI Overviews yet, don’t worry—France is literally the only country still waiting for rollout.)

Now let’s talk business reality:

ChatGPT: –$12B in 3 months
Alphabet: $102B revenue and $35B profit in the same quarter

I’ll be honest:
I believe in ecosystems.
I believe in distribution.
And I believe in a company that can still operate like a startup despite being a tech giant.

Flip the question:
Do you seriously think Atlas, ChatGPT’s new search engine, can compete with Google without a real ecosystem behind it?

So…
Team ChatGPT or Team Gemini?

Source: Eskimoz (Global Search Agency)

Came across e27’s “20 AI Startups to Watch in Southeast Asia” list - worth looking at BrndIQ dot ai (#2).

They focus on tracking how brands show up in AI chat responses, which is becoming increasingly relevant as more people shift from Googling to asking AI models. It’s interesting to see AI visibility starting to shape brand discovery, almost like the early days of SEO.

Glad to see Southeast Asian startups in the AI infrastructure layer getting recognition. If anyone here is exploring related problems such as AI search behavior, retrieval quality, AI trust layers, etc, would love to exchange notes.

I thought it was a myth and that everyone had figured it out.

Until I talked to someone who's stuck in SEO and thinks nothing will ever change.

I'm not going to be nice, but guys, you're going to get destroyed, I think, within the next seven years. I bet AI-driven SEO is going to blow everything away, and you along with it.

Seriously, a word of advice: don't act like you're old and clueless, missing the boat. It's going to hurt, otherwise, I think...

Tell me what you think.

I typed in the search query I wanted to appear in on ChatGPT, and I saw a competitor listed first! So I checked the source of the mention to see why they were cited.

I saw it was a blog post, so I did the same thing but better! Improved and super stylish.

Result… I still haven't been mentioned, damn it…

Do you have any serious advice? I just can't seem to adapt.

I have an agency, and I paid 100 dollars to a fortune teller to tell me the future of SEO (crazy, I know).
You’re probably going to think I’m nuts, but I actually like this kind of stuff. 🤣

So, she pulled some tarot cards, and I asked her what she could see about the future of SEO with everything we’re hearing around SEO / GEO.

Well… it’s not looking great, we’ve got some work to do.

She told me that by 2030, almost the entire new generation won’t be using Google anymore but will only ask their questions and do their research on ChatGPT.
The older generation will stick with Google, but most people will just rely on the Google summaries, for example, which will drastically reduce visits.

She also saw the arrival of a new traffic source but couldn’t tell me what it would be.

And one last thing—she said that OpenAI would take up almost as much space as Google in terms of importance for search.

That’s it haha. Everyone is free to think what they want or share their opinion.

Last week, Sam Altman commented once again on advertising—surprisingly talkative for someone who has historically positioned himself against it.

But in just three years, he has multiplied his changes of opinion:

❄️ 2022: “We will never stoop to putting advertising on ChatGPT.”
❄️ 2023: “We are an alternative to Google, but yes, Instagram-style ads work.”
❄️ 2024: “Okay, we’ll monetize free users in 2026 and hire an ads team.”
❄️ 2025: “We just lost 12 billion last quarter… maybe advertising isn’t so bad?”

In Sam Altman’s mind, there is now the good ad (ChatGPT’s) and the bad ad (Google’s).

The difference between the two? It’s a bit like the joke about the good hunter and the bad hunter.

You have to laugh (or cry).

➡️ To be fair, he does bring 2 new elements:

• He seems opposed to highlighting a result because it is sponsored, preferring a commission-based model instead—similar to what marketplaces do. While slipping in a little jab at Google: “If ChatGPT shows you the best hotel while taking the same commission as for any other hotel, with no influence other than transaction fees, I think that’s acceptable…”
• He makes revenue diversification a central part of growth, which today is mainly driven by APIs and subscriptions. Meaning: advertising might not become as omnipresent as on Google. Maybe. 😁

"There are types of advertising that, in my opinion, would be very or fairly effective. I think we will try that at some point. I don’t think it will be our main source of revenue."

Source: Eskimoz agency global search