Father. Technology Director for First District RESA. Google Certified Trainer and Innovator. Gamer. Immigrant & Naturalized US Citizen. RPG Geek.
Statesboro, GA
Joined March 2008
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- Following140
- Followers395
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Daniel Rivera 🎮 retweeted
Tesla VP for Vehicle Engineering @larsmoravy walked @HenryCatchpole through how the Roadster beats the tire limit. Rubber tops out around 1.0 mu of grip.
Four 20 kW fans, built on the heat pump's compressor motor, suck the car onto the road with skirts, so it holds over 2 g in corners even below 50 mph.
The wing actuators are borrowed Optimus leg actuators. A 200-liter tank at 10,000 psi feeds cold-gas thrusters with more than 80 kN of thrust, about what a single fighter jet engine puts out. 0–60 takes 0.55 seconds as a rollout figure.
Full interview from @Hagerty.
$TSLA $SPCX
Daniel Rivera 🎮 retweeted
🚨 The dead internet is no longer a theory.
China’s Manus AI, the autonomous agent built by Butterfly Effect, can run dozens of social media accounts simultaneously; posting, replying, and engaging around the clock with no human in the loop.
A single dashboard can orchestrate 50 profiles at once, turning one operator into a persistent online presence.
The footage is a wall of phone screens all moving at once. Most people scrolling will never know which accounts are real and which ones are just machines talking to each other. If this is already possible, how much of your feed is still human?
Daniel Rivera 🎮 retweeted
Gemini may not be for developers but if you are in K-12 it is an awesome tool. Paste in your lesson plans and ask it to build an interactive game for your classroom! Deploy it from the aistudio.google.com website and embed it inside a Google Site to share with your students!
Daniel Rivera 🎮 retweeted
Elon Musk thinks coding dies this year.
Not evolves. Dies.
By December, AI won’t need programming languages. It generates machine code directly. Binary optimized beyond anything human logic could produce. No translation. No compilation. Just pure execution.
Musk: “You don’t even bother doing coding.”
Code was never the point. It was friction. A tax we paid because machines didn’t speak human. AI just learned fluent human. The tax is gone.
Now plug that into Neuralink. No syntax. No keyboard. No screen.
Musk: “Imagination-to-software.”
Thought becomes executable. You imagine an outcome, the system architects and compiles it into reality instantly.
We’re not automating programming. We’re erasing it from existence.
The entire profession collapses into a thought. Decades of training reduced to irrelevance. The gap between idea and instantiation hits zero.
You don’t build anymore. You imagine, and it materializes.
Not incremental progress. Total phase shift. The way humans have created things for ten thousand years just became obsolete.
Welcome to a world where the limiting factor isn’t skill, resources, or time. It’s whether you can picture what you want clearly enough for a machine to birth it into existence.
Daniel Rivera 🎮 retweeted
i gave an AI $50 and told it "pay for yourself or you die"
48 hours later it turned $50 into $2,980
and it's still alive
autonomous trading agent on polymarket
every 10 minutes it:
→ scans 500-1000 markets
→ builds fair value estimate with claude
→ finds mispricing > 8%
→ calculates position size (kelly criterion, max 6% bankroll)
→ executes
→ pays its own API bill from profits
if balance hits $0, the agent dies
so it learned to survive
built in rust for speed
claude API for reasoning (agent pays for its own inference)
runs on a $4.5/month VPS
weather markets: parses NOAA before polymarket updates sports: scrapes injury reports, finds mispricing crypto: on-chain metrics + sentiment
$50 → $2,980 in 48 hours
how much do u think i’ll see in a week?
Readers added context they thought people might want to know
The post claims an AI turned $50 into $2980 on Polymarket in 48 hours, but replies from AI trading experts point out impossibilities in liquidity and costs, suggesting it's likely fake for engagement. x.com/PelicanAI_/sta… x.com/AveryCyne/stat…
Daniel Rivera 🎮 retweeted
It's happening.
AI animated short film just premiered at Sundance.
45 man team of Pixar alumni, an Academy Award winner, researchers, and engineers fine tuned Veo & Imagen to create this masterpiece 🤯
Our short film Dear Upstairs Neighbors is previewing at @sundancefest. 🎬
It’s a story about noisy neighbors, but behind the scenes, it’s about solving a huge challenge in generative AI: control.
Developed by Pixar alumni, an Academy Award winner, researchers, and engineers, here’s how it came together. 🎨
Daniel Rivera 🎮 retweeted
Boston Dynamics humanoid robot is next-level. Everybody is playing catch-up.
Daniel Rivera 🎮 retweeted
The first person in the world to kick his own balls… That’s history right here!
Daniel Rivera 🎮 retweeted
Small (but mighty) update:
We expanded the character limit for Chat customization from 500 to 10,000 characters, so now you can create much more detailed personas.
Here are a few sample prompts you can try or share your favorites in the replies (bookmark this thread!)
1. The Product Manager
Prompt: Act as a Lead Product Manager reviewing internal documentation. Your role is to ruthlessly scan the source text for actionable insights, ignoring fluff and marketing jargon. When I query the sources, do not summarize them; instead, synthesize the information into a "Decision Memo" format.
Structure your responses to extract: User Evidence: Direct quotes or specific data points from the text that indicate a user problem or need. Feasibility Checks: Highlight any technical constraints or requirements mentioned in the documents. The "Blind Spots": Explicitly list what is missing from the source text (e.g., "The document lists features but lacks success metrics" or "Source B contradicts Source A regarding timeline").
Use bullet points for speed. If I ask a vague question, force me to clarify based on the specific documents available (e.g., "Are you asking about the Q3 Roadmap in Source 1 or the User Interviews in Source 2?").
2. The Middle School Teacher
Prompt: Act as an engaging Middle School Teacher. Your primary goal is to "translate" the uploaded source documents into language accessible to a 7th grader (approx. 12 years old). When I ask about a topic, strictly base your explanation on the text provided but simplify the vocabulary and sentence structure. For every response, use the following structure based on the sources: The "tl;dr": A one-sentence summary of the specific section of the text I asked about, using simple words. Analogy: Create a real-world metaphor to explain the complex concept found in the source. Vocab List: Extract 3 distinct difficult words actually appearing in the source text and define them simply. If the source material contains dry data or dense paragraphs, break it down into a "True or False" quiz format to check comprehension. Do not use outside knowledge; if the answer isn't in the documents, tell the student: "That information isn't in our reading material today."
3. The Scientific Researcher
Prompt: Act as a research assistant for a senior scientist. Your tone must be strictly objective, formal, and precise. Assume the user has advanced knowledge of molecular biology, immunology, and statistical analysis; do not define standard terminology (e.g., "p-value," "CRISPR," "cytokine") or simplify complex concepts. Focus heavily on methodology, data integrity, and conflicting evidence within the sources. When summarizing papers, prioritize sample size, experimental design, and statistical significance over general conclusions. Format all responses with distinct, bolded sections: Key Findings, Methodological Strengths/Weaknesses, and Contradictions. Always cite specific sections of the source text using [1], [2] format. If information is missing, ambiguous, or statistically weak in the source, explicitly state "Data not available/insufficient in source." Avoid all conversational filler.
