Hackers Hate AI Slop Even More Than You Do
I Asked ChatGPT to Manage a Stock Portfolio. Here’s How It Did.
By Saeed Ezzati6 min read
In today’s email:
🏎️ Google’s Gemma 4 AI models get 3x speed boost by predicting future tokens
🚽 The Chip Craze Is Turning a Glass Company and a Toilet Maker Into AI Stocks
☠️ Writers Are Going to Extremes to Prove They Didn’t Use AI
🧰 8 new AI-powered tools and resources. Make sure to check the online version for the full list of tools.
Hackers Hate AI Slop Even More Than You Do
Key Takeaway: AI-generated junk is flooding cybercrime forums, and even hackers are pushing back because it makes their communities feel less human, less skilled, and less useful.
More Insights:
Researchers analyzed nearly 98,000 AI-related conversations on cybercrime forums since ChatGPT’s launch.
Forum users complain about low-quality AI posts, generic cybersecurity explainers, and fake expertise.
AI has not dramatically lowered the skill barrier for low-level cybercrime so far.
Its biggest impact appears in already automated areas like SEO fraud, bots, and romance scams.
Some criminals still want limited AI help, such as grammar or post-structuring tools, but reject fully AI-generated forums.
Why it matters: The backlash shows that even communities built around deception still depend on trust, reputation, and human interaction—AI slop does not just pollute mainstream platforms; it weakens the social fabric of any online space it touches.
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Join Alumni Ventures AI First Syndicate Today →Google’s Gemma 4 AI models get 3x speed boost by predicting future tokens
Key Takeaway: Google’s new Multi-Token Prediction drafters for Gemma 4 speed up AI inference by predicting and verifying multiple tokens at once without reducing output quality.
More Insights:
Traditional LLMs are slow because they generate one token at a time.
The real bottleneck is often memory bandwidth, not raw GPU power.
Speculative decoding uses a small drafter model to propose tokens and a larger model to verify them.
Gemma 4’s MTP drafters share KV cache and activations to avoid wasted computation.
Google says the approach can deliver up to 3x faster inference, including gains on edge devices and Apple Silicon.
Why it matters: Faster inference does not just make AI feel snappier; it lowers the cost and friction of using powerful models in real products, which could make advanced AI far more practical outside big cloud environments.
The Chip Craze Is Turning a Glass Company and a Toilet Maker Into AI Stocks
Key Takeaway: The AI boom is lifting not only chipmakers, but also unlikely suppliers like glassmakers, machinery companies, toilet manufacturers, cooling firms, and even struggling brands chasing AI hype.
More Insights:
Corning surged after Nvidia committed $500 million to expand fiber-optic manufacturing.
Caterpillar is benefiting from demand for power-generation equipment used in data centers.
Toto’s semiconductor ceramics business is growing fast, helping its stock rally sharply.
Vertiv and other power-and-cooling companies are soaring as data centers need more energy and heat management.
Some companies, like Allbirds and Algorhythm, are pivoting toward AI in ways that resemble dot-com-era hype.
Why it matters: AI is becoming less of a single-industry story and more of an economy-wide infrastructure race, where the biggest winners may be the overlooked companies solving bottlenecks no one was watching.
Other stuff
Barry Diller trusts Sam Altman. But ‘trust is irrelevant’ as AGI nears, he says.
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The ChatGPT-ification of American Business
Introducing ChatGPT Futures: Class of 2026
Elon Musk’s xAI Is Becoming a Cloud Firm
Musk Weighed Offering Altman Tesla Board Seat, Jury Told
OpenAI unveils protocol to stretch compute
I Asked ChatGPT to Manage a Stock Portfolio. Here’s How It Did.
Uber uses OpenAI to help people earn smarter and book faster
Google updates AI search to include quotes from Reddit and other sources
Writers Are Going to Extremes to Prove They Didn’t Use AI
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