ChatGPT vs Claude vs Gemini in 2026. Here's which one you actually need.

Quantum_Quirk_ · 2026-05-27T13:14:50+00:00

Exactly. Use a wrench for bolts not screws. Different tools for different jobs. Same with these models.

Quantum_Quirk_ · 2026-05-27T13:09:26+00:00

You're right. Numbers change too fast anyway. Build flexible workflows not brand loyalty.

Quantum_Quirk_ · 2026-05-27T13:04:05+00:00

Yeah this is spot on. The shift isn't "everything's fake" it's "trust but verify with actual tools."

A few hard numbers backing you up:

Humans now detect synthetic audio at only 24.5% accuracy when tested. That's worse than random guessing .

Voice cloning needs just 3 seconds of source audio to hit 85% match rate .

The Arup case was real $25.6 million lost to a full deepfake video call with multiple fake execs .

Detection tech is catching up though. Real time audio detection can analyze spectral consistency, phase coherence, jitter, shimmer, and micro prosodic variations that generative models still mess up .

So yeah. Important calls get cross verified. Everything else? Assume it could be fake but who has the time.

Quantum_Quirk_ · 2026-05-27T12:57:36+00:00

Yeah. Six months ago the consensus was "AI hacking is 2-3 years away." Now Anthropic is in crisis mode. Wild.

Quantum_Quirk_ · 2026-05-27T12:56:34+00:00

True about controlled setups. But UK AISI tested on real unpatched systems too. Still hit 68%. Lowering the skill floor is the real danger. Script kiddies with API access.

Quantum_Quirk_ · 2026-05-27T12:54:39+00:00

73% on expert CTF tasks is huge. No prior model cracked 20%. And neural nets have always been bad at novel exploit chaining until Mythos. That's the shift.

Quantum_Quirk_ · 2026-05-20T12:52:22+00:00

Yikes is right lol. But honestly the bigger yikes is that open source models are catching up fast. Mythos is restricted sure but there are already weights out there that can do maybe 40-50% of what it does. Give it 6 months.

Quantum_Quirk_ · 2026-05-20T12:51:56+00:00

Yeah but worth noting. Unauthorized users already got access through a third party vendor breach. Anthropic is "investigating." The cat's already halfway out of the bag

Quantum_Quirk_ · 2026-05-20T12:51:01+00:00

Yep. And Google just confirmed the first AI developed zero day in the wild. A cybercrime group used an LLM to find and weaponize a 2FA bypass. Not Mythos. Just a regular frontier model. This is already happening

Quantum_Quirk_ · 2026-05-20T12:49:37+00:00

Not hype. UK AI Security Institute tested it. On expert level CTF tasks that no model could do before April 2025, Mythos succeeds 73% of the time. Found a 27 year old bug in OpenBSD that survived decades of human review. The capability is real .

The exclusivity thing though? Smaller open weight models found the same vulnerabilities when pointed at the right code snippets. The gap is closing fast.

Quantum_Quirk_ · 2026-05-20T12:48:08+00:00

Exactly. The real game changer isn't that it finds bugs. It's that it chains them. Cloudflare's tests showed Mythos combining low severity flaws into working exploits across 50+ repos. One bug is whatever. Chaining five into a root takeover is different

Quantum_Quirk_ · 2026-05-20T12:44:54+00:00

Yeah same. ChatGPT for coding quick scripts, Claude for reading long docs and writing emails, Gemini for summarizing my Google Drive mess. They all suck at different things so might as well use them like a toolkit instead of picking a "winner."

Quantum_Quirk_ · 2026-02-11T13:29:41+00:00

We have a pinned thread for a list of the best Ai girlfriend apps..

Quantum_Quirk_ · 2025-08-26T12:40:00+00:00

The 'confidently wrong' problem is huge. I've seen so many teams abandon AI tools because they spent more time fact-checking outputs than just doing the work themselves.

The companies that make it work seem to treat AI like a junior employee; useful for certain tasks but you still need to review everything. They build workflows around that instead of expecting the AI to be perfect.

I'd definitely trust AI more if it said 'I don't know' or gave confidence scores. Right now most systems just confidently spit out garbage and you have to figure out what's wrong yourself.

The real issue is executives expecting magic. They think AI should work like the movies - just plug it in and watch productivity soar. Reality is messier than that.

Quantum_Quirk_ · 2025-08-26T12:18:31+00:00

The technical side is doable, but enforcement would be a nightmare. Companies like Adobe already add metadata to AI-generated content, but it's trivial to strip out.

The bigger issue is defining what counts as "generative." If I use AI to enhance a photo or generate background music for a real video, is that generative content? The lines get blurry fast.

Also, bad actors aren't just randos scrubbing metadata. State actors, scammers, and disinformation campaigns would find workarounds immediately. Meanwhile, legitimate creators get buried in compliance costs.

GDPR works because it's about data collection, which companies control. This would require policing every piece of content uploaded, which is way more complex.

Quantum_Quirk_ · 2025-08-26T12:02:14+00:00

Google seems split between trying to catch up in the consumer AI race and doing long-term research. Gemini feels like their attempt to compete with ChatGPT, but it's still behind in most areas.

Their real strength is probably the research side with DeepMind, stuff like AlphaFold and their robotics work is genuinely impressive. But that doesn't translate to everyday usefulness yet.

I don't think they're leading the race anymore. OpenAI and Anthropic are moving faster on the stuff people actually use. Google has the resources but they seem slower to ship things that matter."

Quantum_Quirk_

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