u/ImaginaryRea1ity

How many of you have played with breadboards and microcontrollers?

Last year researchers caught AI trying to make viruses against Jewish people. AI needs to be stopped before it causes real harm.

BIOS, windows, dial up the whole shebang!

Luke Dicken spent a decade at Zynga building AI R&D and most recently led AI across all of Take-Two Interactive, the publisher behind GTA, NBA 2K, and Borderlands, before his entire team was laid off. This is an in-depth interview published on 80 . lv, a professional game development resource.

What Dicken says is genuinely happening versus what studios are selling to executives:
🔹 The "magic button that automates entire pipelines" does not exist in any generalized, meaningful way. What does exist is useful for boring, repetitive tasks that have no bearing on whether a game succeeds
🔹 GitHub Copilot's move from flat subscription to usage-based pricing revealed 10x to 1,000x cost jumps for some users, the moment the subsidy came off. The same reckoning is coming for every AI tool in production pipelines right now
🔹 AI's non-determinism is a serious production problem: the same prompt does not produce the same output, and model weight updates by providers can silently change behavior in live pipelines

Where Dicken sees the real opportunity that almost nobody is building toward:
🔹 A true "AI Dungeon Master" that profiles players, adjusts pacing, manages narrative tension, and personalizes the experience end-to-end. The technology exists in pieces. Nobody has assembled the whole thing yet
🔹 The studios that will define the next decade are the ones asking what new player experiences AI enables, not how cheaply it can replace someone

"The studios that realize the real goal shouldn't be to squeeze the human workforce but instead harness technology to amplify that workforce's creative reach are going to be the ones that define the next decade of play."

Dicken's read: AI costs are still subsidized. Once the real price hits, studios that deployed AI without measuring ROI will have no idea whether to keep paying. That is not a distant risk. He puts it at 18 months.

If you want to support game devs while on a budget, check out 90 or Nothing. Every week they email you a list of all games on Steam with 90% discount.

The initial list (and the image below) was missing a number of groups and I am adding them to the list after each comment. It's truly fascinating how many we are!

🇫🇷 Mistral, CroissantLLM, LightOn, Inria
🇩🇪 Germany Soofi, OpenGPT-X, Aleph Alpha
🇪🇺 EuroLLM, OpenEuroLLM, Occiglot
🇵🇱 SpeakLeash | Spichlerz, Slayer Lab, PLLuM
🇳🇴 LTG - Language Technology Group, Nasjonalbiblioteket | The National Library of Norway AI Lab
🇨🇿 BottleCap AI
🇺🇦 Lapa LLM
🇧🇬 INSAIT - Institute for Computer Science, Artificial Intelligence and Technology
🇩🇰 Danish Foundation Models
🇫🇮 TurkuNLP
🇬🇷 ILSP
🇮🇹 Sapienza NLP
🇵🇹 Unlabel
🇪🇸 Barcelona Supercomputing Center
🇸🇪 AI Sweden
🇨🇭 Swiss AI Initiative with Apertus
🇬🇧 BritLLM
🇸🇮 CJVT with GaMS

Whom am I still missing? Did I mislabel somebody? I initially added AI Desktop 98 to this list, but I’m not sure if they’re European.

He spent 26 minutes live on stage doing what most teams take weeks to do.

No team, no setup, just Claude and a goal. Worth more than any $500 vibe coding course.

Those who learn what Claude really does are launching what everyone else outsources to a team.

The gap between what AI can do and who knows how to use it is the biggest opportunity in the market right now.

Engineers will always be engineers. You are born an engineer, not made.
AI won’t change that.

It’s called watermarks-remover, it’s 100% open-source, and it targets several layers of AI provenance:

→ Invisible Unicode characters get stripped
→ C2PA metadata can be removed from images, PDFs, and documents
→ Statistical text watermarks are attacked by rewriting the output

And that exposes the core problem with AI watermarking:

↳ The defender has to build a signal that survives almost everything.
↳ The attacker only has to find one way to break it.

C2PA can cryptographically prove where a file came from, but the metadata can disappear when a file is re-encoded, screenshotted, or cleaned.

Statistical watermarks are harder to remove, but enough paraphrasing can weaken the patterns they rely on.

So the watermark starts looking less like a lock and more like a tamper-evident sticker.

And the hiring signals from the biggest companies suggest the market is about to move fast.

Monthly tech layoffs from September 2025 through August 2026.

March was brutal: 50,404 people got cut in a single month. Oracle, Dell, Meta, and a handful of others all moving at once. May was almost as bad at 34,639, with PayPal, Cisco, Intuit, and Walmart added to the pile.

Then the pace changed.

June dropped to 8,963.
July came in at 14,117.
August so far is running at 2,753, and there are still 18 days left in the month.

Even if it doubles from here, it'll still be the calmest month the market has seen in almost a year.

To be clear, 2026 has been a hard year. Total layoffs have already passed 2025's full-year number with four months still on the calendar.

But the intensity has clearly come off, and the hiring side of the market is already turning.

Google posted 62% more engineering roles in the first half of 2026 than the same period last year. Apple has more open engineering roles than it did a year ago. Q1 2026 hit 67,000 SWE openings, the highest since early 2023.

Stripe, Shopify, and Atlassian are all hiring faster than most of Big Tech.

The pattern is clear if you're watching for it. Layoffs cooling. Hiring warming.

Most job seekers give up right before the doors open again.

If you're still in it, don't slow down now.

Here’s a demo.

But ai haters will still say it has no use.

The tech hiring recovery everyone was calling last year is real. It just isn't happening for everyone.

2026 has been the strangest job market for SWEs I've ever watched.

Here's the chart most people saw.

Software engineering headcount at the top 5 companies from 2020 to 2025. Boom, bust, recovery.

By late 2025, Meta was back at 2022-level headcount growth. Google, Apple, Amazon, and Microsoft all trending up.

The story looked clean. And then 2026 happened.

Both of these are true right now:
67,000 SWE openings in Q1 2026, the most since early 2023.
143,000 tech workers laid off through May.

Amazon cut 30,000 corporate and tech roles between October 2025 and January 2026. Meta did a 10% cut in mid-2026 after two years of aggressive hiring, and reassigned thousands of engineers to data labeling.

At the same time, Google posted 62% more engineering roles in the first half of 2026 than the same period a year before.

It's not a recovery, or a collapse. It's a split.

ML engineer openings are up 59% from their pre-pandemic baseline.
General SWE openings are still 49% below theirs.

Senior engineers with cloud, security, or AI experience are closing offers in 2 to 4 weeks. Generalists and early-career engineers are taking months, sometimes longer.

Radiology is highly paid, much of the work involves pattern recognition, there’s enormous amounts of training data, and AI has been remarkably good at medical imaging for years.

Geoffrey Hinton thought so too. In 2016, he famously suggested we should stop training radiologists because deep learning would soon outperform them.

So I assumed radiologist salaries must at least have taken a hit.

I looked it up.

Average compensation for US radiologists is now about $570,000, putting it among the highest-paid specialties in medicine.

There’s a shortage of them.

That really surprised me.

AI can read scans. But the number of scans isn’t fixed. As imaging gets easier and more useful, we started doing more of it.

And a radiologist isn’t just a very expensive image-recognition system. There’s a licensed human at the end of the process 𝗺𝗮𝗸𝗶𝗻𝗴 𝗮 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻 𝗮𝗻𝗱 𝘁𝗮𝗸𝗶𝗻𝗴 𝗿𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝘆 𝗳𝗼𝗿 𝗶𝘁. And that is the key.

I’m not convinced radiology is somehow immune to AI. Quite the opposite. It seems like one of the professions AI is transforming the most.

Tool like AI Desktop 98 can help software engineers write software but they cannot replace human judgement.

I use AI Desktop 98 to use open source ai models on my Mac and avoid making Dario richer.

ChatTJB is a performance art project by Tucker Bryant, a conceptual artist and former Google employee.

He rented the SoMa billboard for $6,000 a month.

Bryant reads the messages himself and types back answers, sometimes for 10 hours a day, and draws requested images by hand.

After the billboard went up on July 27, traffic peaked at 5,000 prompts per hour, and the project logged over 30,000 queries by August 6.

Bryant says the goal is to make people pause before accepting chatbot answers at face value.

If you want real, local AI try AI Desktop 98.

😂

Stanford's famous "canaries" study found AI's employment effects confined to workers 22–25 — older groups showed "much less marked differences." That was accurate when their data ended.

So I re-ran the analysis on the current public data, through June 2026.

In the most AI-exposed occupations, four of the six age bands are now clearly past their employment peaks.

And they turned in order of age:
→ 22–25: peaked first (late 2022), now at 88 on the index
→ 26–30: peaked November 2024, now below their 2022 level
→ 31–34: peaked November 2024, down >3 points
→ Even 50+ has been sliding since late 2025
→ Two groups are still at their peaks but appear to be plateauing: workers 35–40 and 41–49

Sticking with the canary metaphor, we can see the gas rising through the mine.

Experience buys time, but might not buy immunity.

https://techbronerd.substack.com/p/trump-era-white-male-dei-just-cost

Interesting article talking about the recent Bitcoin wallet hack and why anti-H1b stance ends up hurting Americans.

Another win for WiT