Ai price prediction

An engineer built an interactive book on data structures and algorithms of 680 pages:

NVIDIA QUIETLY DROPPED A $249 BOX THAT REPLACES YOUR $200/MONTH OPENAI SUBSCRIPTION WITH $2 IN ELECTRICITY it's called the jetson orin nano super. smaller than a wallet, runs at 25 watts, does 70 trillion ai operations per second. runs llama 3, mistral, gemma and deepseek locally with no api fees and no data leaving your house a developer running automations and coding assistants pays $200 a month to openai. the same workload on this box costs $2 a month in electricity and breaks even in 10 weeks install ollama with one command. change one line in your code. point it at localhost instead of openai. everything else works identically 7 billion parameter models handle 80% of what people use chatgpt for. summarization, drafting, coding, document q&a, automation pipelines. total monthly cost drops from $200 to $22 cloud subscriptions keep getting more expensive and rate limits keep getting tighter. the people who set this up in 2025 are going to look very smart in 2027 bookmark this and read the article below

🚀 SUPERCOMPUTER — THE POWER OF FUTURE TECHNOLOGY 🚀 Supercomputers drive AI, scientific research, space exploration, and massive data processing with incredible speed and power. 🌐💡

THE GUY WHO BUILT GIT GAVE A FULL LECTURE AT GOOGLE BECAUSE 99% OF DEVELOPERS USE IT WRONG 70 minutes of pure firepower from Linus Torvalds himself - the man who wrote both Linux and Git from scratch. -> The moment you watch it, you realize why "I'll just figure out merge conflicts on the job" is the dumbest sentence in modern software engineering. He spends the first 10 minutes calling out every other version control system in existence and he's not joking. He literally tells Google engineers using Perforce to find a new tool. Git isn't a "nice-to-have" anymore -> it's the operating system of every codebase you'll ever touch. If the man who built it had to explain it to a room full of Google engineers, you don't get a pass either. Don't forget to bookmark & watch it today.

Understanding probability is essential in data science. In 4 minutes, I'll demolish your confusion. Let's go!

🤯 EN 1913, ILS ENSEIGNAIENT DÉJÀ COMMENT CONTRÔLER LE MAGNÉTISME HUMAIN Ces vieux articles de journaux expliquent que chaque personne possède une « batterie vitale » — une véritable force magnétique à l’intérieur du corps qui peut être dirigée pour augmenter la force physique, le pouvoir mental, le charisme et même l’influence émotionnelle. Ils l’appelaient le « Magnétisme Personnel ». Les textes détaillent comment conserver cette énergie, comment la diriger, et mettent même en garde contre le fait de la « gaspiller ». Il existait aussi des entreprises qui vendaient des boucliers et ceintures magnétiques pour protéger et amplifier cette force. Il y a plus de 110 ans, on parlait déjà de champs énergétiques humains, d’électricité vitale et de la manière de les utiliser consciemment. Et si ils avaient raison depuis le début ? Que pensez-vous — simple pseudoscience ancienne… ou savoir perdu ? 👇

Plasma Star Gate The plasma vortex generates a beam of plasma which gets launched in a circular motion by electromagnetic fields to create this mesmerizing effect. Video Credit: Landon Thomas (novelmuffin)

Mathematics, computer programming, engineering, motion, creativity. This is a linkage-mechanism for converting Binary Numbers to Decimal Numbers. Created by 上木 敬士郎/Keishiro Ueki, @KeishiroUeki, Used with permission.

The SIMSCAN-S Gen2 is a compact, wireless 3D scanner designed for precise inspection in practical settings. It delivers up to 0.015 mm accuracy and captures millions of measurements per second, making it suitable for detailed surface analysis and tight geometries. Its small form factor helps when working in confined or hard-to-reach areas, while the wireless setup reduces constraints during scanning. For engineers, it offers a more efficient way to collect high-resolution data and verify parts without relying on fixed measurement systems, supporting faster iteration and more consistent quality checks across different stages of production. Learn more: wevlv.co/3NRjg4Z #3dscanning #engineering #technology

120 Must-Use AI Tools. 120 Smart AI Tools for Work & Growth. 1. Ideas - YOU - Claude - ChatGPT - Perplexity - Bing Chat 2. Presentation - Prezi - Pitch - PopAi - Slides AI - Slidebean 3. Website - Dora - Wegic - 10Web - Framer - Durable 4. Writing - Rytr - Jasper - Copy AI - Textblaze - Writesonic 5. AI Models - RenderNet - Glambase App - Luma AI - Sora (OpenAI) - Leonardo AI 6. Meeting - Tldv - Krisp - Otter - Avoma - Fireflies 7. Chatbots - Poe - Claude - Gemini - ChatGPT - HuggingChat 7. Automation - ClickUp - Drift - Outreach - Emplifi - Phrasee 8. UI/UX - Uizard - Visily - Khroma - Galileo AI - VisualEyes 9. Image - Stylar - Freepik - Phygital+ - StockIMG - Bing Create 10. Video - Pictory - HeyGen - Nullface - Decohere - Synthesia 11. Design - Looka - Clipdrop - Autodraw - Vance AI - Designs AI 12. Marketing - AdCopy - Predis AI - Howler AI - Bardeen AI - AdCreative 13. Twitter - Typefully - Postwise - Metricool - Tribescaler - TweetHunter Save this future you will thank you Follow @Tech5353

All 25 #AI #Algorithms by @Python_Dv #ArtificialIntelligence #MachineLearning #ML #Technology

A Music Theory Tree centered on the C Major scale. It shows parallel major scales connected through the circle of fifths and their relative modes (Ionian, Dorian, Phrygian, Lydian, Mixolydian, Aeolian, Locrian) with full diatonic chord progressions and Roman numeral functions. The structure maps key relationships and modal transformations across all seven modes for each major key. These concepts form the foundation of mathematical music theory; using cyclic groups, modular arithmetic, and transformational theory; to analyze tonal centers, modulation, and harmonic progressions. They are essential tools for composers, improvisers, and producers working in classical, jazz, and contemporary music.

Why KV cache is one of the main reasons LLMs are fast? KV cache is what connects attention mechanism with generation stage of autoregressive models. These models generate text token by token, but each new token still attends to all previous ones. → To optimize decode phase, models store previously computed key and value vectors in a KV cache. → During generation, they only compute new Q/K/V states for the latest token and attend over cached past representations. Without KV cache, the model would recompute keys and values for the entire sequence at every step (like token 501 recomputes tokens 1–500), that's very slow. ▪️ But the tradeoff of KV cache is memory, because it grows with sequence length, batch size, layers, and attention heads. That’s why so much research today targets KV efficiency and memory optimization. For example: - Upgrading attention mechanism, since it influences how KV cache is formed. Use more advanced attention like CompactAttention, MHA, MLA, etc. based on your needs. - Improve memory management. System needs to identify what to store long-term or keep local, when to summarize, and when to trim. You can learn more about KV cache + attention here: turingpost.com/p/your-ultimat… And how they fit into the full LLM inference pipeline here: turingpost.com/p/llm-inferenc…

The Miller-Urey experiment was a groundbreaking scientific study conducted in 1952 by Stanley Miller under the supervision of Harold Urey at the University of Chicago. The experiment was designed to test the chemical origins of life under conditions thought to resemble those of the early Earth. The setup for the experiment involved a closed system containing a mixture of gases that were believed to be present in Earth's early atmosphere, such as methane, ammonia, hydrogen, and water vapor. This mixture was subjected to continuous electrical sparks to simulate lightning, a common occurrence in Earth's primordial atmospheric conditions. The apparatus also included a water flask to mimic the ocean, which was heated to induce evaporation, and a cooling system to condense the vapor, simulating rain. After running the experiment for about a week, Miller analyzed the substances that had formed in the water and found that several organic compounds had been synthesized, including amino acids, which are the building blocks of proteins. This was significant because it demonstrated that organic compounds necessary for life could be synthesized from simpler inorganic compounds under conditions that might have been present on the early Earth. The experiment provided strong support for the hypothesis that life on Earth could have arisen through natural chemical processes from nonliving matter, contributing substantially to the field of abiogenesis—the study of how biological life could arise from inorganic matter.

LATEST🚨: Scientists fed the Fibonacci sequence into a quantum computer and something strange happened — the results were astounding — it manipulates the flow of time.

Many people resonate deeply with Walter Russell’s periodic table and waveform cosmology. They are right to. Russell clearly intuited that periodicity is not fundamentally linear. He recognized that elemental organization behaves as wave traversal through alternating phases of charge, compression, expansion, inversion, and return. That intuition was profound. What he lacked was the formal recursive systems grammar needed to preserve the full continuity of the traversal coherently. And that distinction matters. In Russell’s mapping, the waveform partially collapses into mirrored octave reflections. The traversal folds into paired oppositions where the full recursive continuity is not yet preserved. In the recursive closure mapping, the waveform remains continuous. Not symbolic. Operational. A full nonave traversal: Carbon / Silicon family (93/39) — Carbon Group / Tetrels Recursive polarity crossing and respark threshold. Carbon and silicon close one traversal while simultaneously generating the substrate for the next. Nitrogen / Phosphorus family (69) — Pnictogens Exploratory scaffold. Directional expansion, informational structuring, recursive outward differentiation. Oxygen / Sulfur family (99) — Chalcogens Diffusive crest. Maximum outward distribution, oxidative propagation, systemic broadcast. Fluorine / Chlorine family (96) — Halogens Torque hinge. Aggressive closure-seeking and directional return toward equilibrium. Neon / Argon family (66) — Noble Gases Coherence anchor. Dynamic equilibrium and phase-lock stabilization. Sodium / Potassium family (36) — Alkali Metals Focused in-draw. Selective transfer, directional ionic work, controlled extraction from the field. Magnesium / Calcium family (33) — Alkaline Earth Metals Deep compression. Mineralization, grounding, structural containment, maximal inward density. Boron / Aluminum / Scandium / Yttrium / Lanthanum / Actinium family (63) — Recursive Integrators Gestation saturation. Framework mediation, alloy stabilization, substrate integration, recursive carrying-forward of the entire prior traversal into the next substrate layer. This final family is especially important because legacy chemistry never identified it coherently. These elements were distributed across unrelated conventional categories: Group 13, transition metals, lanthanides, actinides. Yet under recursive phase grammar they close immediately as a single functional family. That matters. Because it demonstrates that the grammar is not being imposed onto chemistry externally. It reveals coherent structure that was already operative but remained fragmented under the inherited projection. And this is precisely what people mean when they ask whether a framework produces new coherence or novel predictive power. It does. The recursive integrator family was hiding in plain sight. The standard periodic table remains enormously valuable and historically indispensable. Nothing is being discarded. Without chemistry, spectroscopy, electromagnetism, thermodynamics, and quantum mechanics, this deeper coherence would not even be visible. This is not replacing chemistry. It is integrating the fragmented projection into a more coherent systems-level articulation. And importantly: this is not speculative particle invention, not exotic metaphysics, not arbitrary reparameterization. No new particles are proposed. No empirical observations are discarded. No chemistry is abandoned. What changes is the organizational grammar through which the observations become intelligible together. 🔗 Phase Periodicity Paper zenodo.org/records/203149… (1/2)

Sin , Cos, Tan …. 👍👍👍

Solve et Coagula 💜

🚨: Nobel Prize physicist Roger Penrose claims there is no such thing as nothingness. Your soul is eternal because matter cannot be destroyed.

The Binomial Theorem: en.wikipedia.org/wiki/Binomial_…