Generative models, prompting, agents and AI tool capabilities.
Google is BACK! (Gemini 4 Argon - Fully Tested!)
11d ago · English audio
Gemini 4 Argon tested hands-on with early access: I pushed Google's new model to 1 million output tokens in a single response, had it rebuild websites from one screenshot, model a 3D dragon in pure math, and run ML experiments on my DGX Spark GPU. You'll learn how the continuation token works, how to prompt Argon for long outputs, when low, medium or high reasoning effort is worth it, and why your graders belong…
Prompt Engineering
👋 I'm Muhammad! I am an AI/ML Expert with a PhD and have led ML teams at startups over the last 8 years. I am also a Google Developer Expert for ML/AI. The goal of this channel is to share my learning without all the "fluff" and "hype". I offer consulting services to startups and https://calendly.com/engineerprompt/consulting-call…
Outlier score
131.7K views ÷ a 20.3K baseline = 6.5×. Compared with 50 earlier videos from the same channel, matching the format recorded at scoring time. Older-upload baseline: reference videos had at least as long to gain views. This comparison is not age-matched.
YouTube snapshot: Sun, 25 Oct 2026 14:36:32 GMT. Counters may have changed.
Read the methodologyGenerative AI & Agents
Channel-balanced percentile: 88
Comparison details
74 videos from 45 other channels, with each channel weighted equally. Same format and language, with 100,000–999,999 subscribers. Observed at 287 hours after publication, within ±48 hours.
This describes the collected sample, not all of YouTube. Updated Sun, 25 Oct 2026 15:34:19 GMT.
Niches & tags
Predictive models, model training, evaluation and learning algorithms.
Transcripts and detailed analytics are available for recent outlier Shorts up to three minutes. Research tools