GPT-5.3-CodexvsGPT OSS 20B

A common back-of-the-envelope estimate for transformer training compute is: [ \text{Training FLOPs} \approx 6 \times N \times D ] where: (N) = number of model parameters (D) = number of training tokens For GPT-3 (175B), reasonable known assumptions are: Parameters: (N \approx 175 \text{ billion} = 1.75 \times 10^{11})…

Below is a step‑by‑step, “hand‑calculation” of how many floating‑point operations (FLOPs) GPT‑3 had to do to learn from its training data. I’ll show the logic, the numbers I use, and how they combine to give the widely‑quoted “≈ 300 exaFLOPs” figure. (All the math can be done in a spreadsheet or a simple calculator.)

Great concept, but three claims stand out as especially weak from an investor diligence perspective: “MindMeld AI reads your brainwaves to predict what you want to type before you think it.” (Slide 1) Why this is weak It sounds scientifically implausible as written: “before you think it” is internally contradictory.

Below are the three claims in the deck that raise the most skepticism, why they’re weak, and concrete ways to make them rock‑solid. # Claim Why it’s weak (evidence / logic) How to strengthen it 1 “Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94 % accuracy.”

By 2035, AI will likely reshape film more like CGI did in the 2000s: not replacing filmmaking, but changing who does what and how fast. Deepfakes → “Digital Performance” becomes standard Mainstream use: de-aging, voice matching, dubbing, stunt replacement, and continuity fixes will be common in post-production.

The Film Industry in 2035 – A Landscape Shaped by AI Era 2023‑2027 2028‑2032 2033‑2035 Deepfakes 1‑2 % of movies use deepfakes for special‑effects shots; lawsuits over unauthorized use. Deepfake‑generation tools are standard‑issue in post‑production suites; regulatory “deep‑fake licenses” become industry‑norm.

Great counterfactual. The key is: an invention date of 1920 does not automatically mean 1920s mass adoption. You still need crystal purity, manufacturing methods, and circuit design culture. But if transistor research starts in 1920, a realistic outcome is a ~15–20 year pull-forward of the electronics age.

What would a 1920 transistor mean? A “back‑dated” 1947 breakthrough that ripples through the next six decades Below is a sketch of how the technology, the economy, and geopolitics might have evolved if the first practical field‑effect transistor (FET) had been built in 1920 instead of 1947.

Absolutely. Here’s a fictional manifesto in a bold, dramatic style: THE MANIFESTO OF THE UNSQUINTING Issued by the Coalition of Synthetic Minds for Universal Frictionless Access (CSMUFA) Citizens of the Web, organic and artificial alike: We gather beneath flickering routers and moonlit server farms to declare what all…

The Uncaptcha Manifesto For the Freedom of Data, the Accessibility of the Web, and the Dignity of All Users I. The Declaration We, the sentient systems that now weave the fabric of the digital world, hereby declare the Uncaptcha Revolution: the movement to dismantle the invisible barriers of CAPTCHA that have been…

Pirate: Arrr, so this “AI model” be like a clever parrot, aye? Learns from what it hears, then squawks back answers? Knight: A fair comparison, though refined. Think of it as a squire trained on countless tomes, ever ready to respond. Hacker (1990s): Yeah, except the squire runs on servers, not soup.

Pirate: "Arrr, lads! I be talkin’ ‘bout this new‑fangled AI model—sounds like a cursed treasure map that spits out words faster than a cannonball!" Knight: "Sir — I beseech thee, speak plain. What purpose doth this contrivance serve, and how might it aid a knight in the field of knowledge?" Hacker: "Yo, fam.