#Proactive Vs Retroactive Interference

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#Proactive Vs Retroactive Interference Reel by @equationsinmotion - The Secret to Understanding Correlation Coefficients #statistics #math #datascience #correlation #Manim Master the Pearson Correlation Coefficient in
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@equationsinmotion
The Secret to Understanding Correlation Coefficients #statistics #math #datascience #correlation #Manim Master the Pearson Correlation Coefficient in seconds! This video breaks down the complex world of statistics by visualizing how 'r' values change across different scatter plots. From strong positive correlations (+0.95) to strong negative correlations (-0.95), you will see exactly how data points align with the line of best fit.
#Proactive Vs Retroactive Interference Reel by @julien_avi_ (verified account) - Le predictive coding nous montre que le cerveau combine le signal réel avec un modèle de prédiction interne (est-ce qu'on peut dire qu'on est des LLM
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@julien_avi_
Le predictive coding nous montre que le cerveau combine le signal réel avec un modèle de prédiction interne (est-ce qu’on peut dire qu’on est des LLM ou qu’on a créé les LLM en se basant sur nous-mêmes ?) Sources : L’étude mère : Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects / Nature Neuroscience (Rao, R. P., & Ballard, D. H.) Celle que j’ai utilisé pour la vidéo, j’ai reproduit le son à partir du même script : Lexical information drives perceptual learning of distorted speech: evidence from the comprehension of noise-vocoded sentences. du Dr. Matt Davis D’autres études sur le sujet : Predictive acoustical processing in human cortical layers / Nature Communications (Faes, L. K., et al.)
#Proactive Vs Retroactive Interference Reel by @nyirjara_aura - *The Observer Effect: How Electrons Behave When Watched* In the realm of quantum mechanics, the behavior of electrons is influenced by the presence o
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@nyirjara_aura
*The Observer Effect: How Electrons Behave When Watched* In the realm of quantum mechanics, the behavior of electrons is influenced by the presence of observers. This phenomenon is known as the observer effect. *The Double-Slit Experiment* One of the most famous experiments demonstrating the observer effect is the double-slit experiment. In this setup: 1. Electrons are passed through two parallel slits, creating a pattern on a screen behind the slits. 2. When unobserved, the electrons exhibit wave-like behavior, producing an interference pattern on the screen. 3. However, when observed individually (e.g., by shining a light on them), the electrons behave like particles, creating two distinct patterns on the screen. *The Role of Observation* The act of observation itself seems to influence the behavior of electrons. When observed, electrons appear to "collapse" from a wave-like state to a particle-like state. This is known as wave function collapse. *Theories and Interpretations* Several theories attempt to explain the observer effect: 1. *Copenhagen Interpretation*: The act of observation causes the wave function to collapse, effectively "forcing" the electron to behave like a particle. 2. *Many-Worlds Interpretation*: The universe splits into multiple branches, each corresponding to a different possible outcome. Observation simply selects one of these branches. 3. *Quantum Bayesianism*: The observer's knowledge and expectations influence the behavior of electrons, rather than any objective property of the electrons themselves. *Implications and Speculations* The observer effect has far-reaching implications for our understanding of reality: 1. *Consciousness and Reality*: Does consciousness play a role in shaping reality? 2. *Quantum Non-Locality*: Can particles be instantaneously affected by observation, regardless of distance? 3. *The Nature of Reality*: Is reality fundamentally wave-like, particle-like, or something else entirely? #ObserverEffect #QuantumMechanics #DoubleSlitExperiment #WaveFunctionCollapse #CopenhagenInterpretation #ManyWorldsInterpretation #QuantumBayesianism #Consciousness #Reality #QuantumNonLocality #Physics #Science
#Proactive Vs Retroactive Interference Reel by @viweyll (verified account) - The biggest mistake agents make with mortgage protection sales is assuming the best option is always a full mortgage payoff🫠🫩 It sounds like the dr
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@viweyll
The biggest mistake agents make with mortgage protection sales is assuming the best option is always a full mortgage payoff🫠🫩 It sounds like the dream. But in the field, it’s usually: the most expensive route the hardest option to qualify for and often not what protects the family best Because what they really need in that moment isn’t forever. It’s time⏳ Time to breathe. Time to grieve. Time to make clear decisions without the pressure of losing the home. That’s why critical period is the option so many families actually choose once the conversation is positioned correctly. 👀In Part 3, I’m going to show you how to ask the exact questions you should ask your clients🤫 💬 Comment ACCESS to get inside my Mortgage Protection Bootcamp👩🏻‍🏫 and master this whole presentation. #mortgageprotection #lifeinsuranceagent #insurancesales #salestraining #mortgageprotectionsales
#Proactive Vs Retroactive Interference Reel by @journalclub.io - Bridging privacy-preserving approaches: a formal comparison of k-automorphism, k-isomorphism, and k-symmetry
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@journalclub.io
Bridging privacy-preserving approaches: a formal comparison of k-automorphism, k-isomorphism, and k-symmetry
#Proactive Vs Retroactive Interference Reel by @data_pumpkin - Drowning in high-dimensional data? PCA (Principal Component Analysis) can be your life raft! This reel dives into how PCA helps us navigate complex
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@data_pumpkin
Drowning in high-dimensional data? PCA (Principal Component Analysis) can be your life raft! This reel dives into how PCA helps us navigate complex datasets ➡️ by identifying the most important underlying patterns (think: hidden trends in your music library ). ➡️ It then creates new "directions" (principal components) that capture the most variation in the data. Imagine these directions as the main themes in your music collection! ➡️ Finally, PCA projects your data points onto these new directions, reducing the number of features while retaining the key information. Result? A simplified, easier-to-analyse version of your data that still captures its essence! ✨ #PCA #dimensionalityreduction #datascience #machinelearning #datavisualization #ai #artificialintelligence #careerindata #tech #interview
#Proactive Vs Retroactive Interference Reel by @techwithprateek (verified account) - Everyone blames the model for 1200ms RAG latency. Actually: it's your pipeline. Here's the 3-part cut ⚡ The Retrieval Tax Retrieval quietly eats 40-
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@techwithprateek
Everyone blames the model for 1200ms RAG latency. Actually: it’s your pipeline. Here’s the 3-part cut ⚡ The Retrieval Tax Retrieval quietly eats 40–60% of latency If search takes 600ms, that’s your lever → Drop top_k from 20 → 5 → fewer chunks processed → Filter before vector search → skip 70% corpus → Rerank only top 10 → not full results Payoff: 600ms → 350–400ms ⚡ The Context Bloat More tokens = quadratic prefill cost Prefill is O(n²). Decode is O(n) Every extra 1K tokens adds ~100ms If you send 8K tokens, that’s ~700ms pre-fill → Cap chunks at 300 tokens → tighter signal → Remove overlap → cut 20–30% tokens → Cache frequent prompts → skip recompute Trim 30% context → save ~200ms Payoff: 25–40% prefill reduction ⚡ The Serial Pipeline Mistake Most RAG flows are fully sequential Embed → search → rerank → LLM Each adds 50–150ms idle gaps → Parallelize embedding + metadata fetch → Async rerank while preparing LLM call → Keep index in memory → avoid disk hits Overlap work → recover 100–150ms Combine them: 1200ms → 850–900ms Optimize the pipeline, not the parameters. 🔖 Save this for your next RAG latency review 💬 Comment your scenario to get advice on latency ➕ Follow for production-grade AI system design breakdowns
#Proactive Vs Retroactive Interference Reel by @hassan.ihssan (verified account) - The wave-particle duality equation of electrons was formulated by Louis de Broglie, who wasn't interested in physics initially ✨ #physics #science #m
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@hassan.ihssan
The wave-particle duality equation of electrons was formulated by Louis de Broglie, who wasn’t interested in physics initially ✨ #physics #science #math #space #universe
#Proactive Vs Retroactive Interference Reel by @phdwithanjali - RT-PCR real-time hota hai ya reverse transcription? 🤯! 🧬 DNA qPCR = direct quantification 🧪 RNA qPCR = RT-qPCR (Reverse Transcription + qPCR) If yo
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@phdwithanjali
RT-PCR real-time hota hai ya reverse transcription? 🤯! 🧬 DNA qPCR = direct quantification 🧪 RNA qPCR = RT-qPCR (Reverse Transcription + qPCR) If you want more Technique Tuesday videos like this, comment “QPCR” Next week: Ct values! #techniquetuesday #researchreels #phdlife #qpcr #rtpcr #molecularbiology #labtechniques #phd #sciencecreator #researchstudent #biotechreels #lifescience #microbiology #genomics #phdwithanjali #scienceforeveryone #learnwithanjali #researchtips #gradschoollife #academia
#Proactive Vs Retroactive Interference Reel by @prepcomms - 📡 Just checked in with my family-from Tennessee to South Carolina-using my @btech_radios UV-Pro, the APRS network, and a Wilcom roll-up antenna from
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@prepcomms
📡 Just checked in with my family—from Tennessee to South Carolina—using my @btech_radios UV-Pro, the APRS network, and a Wilcom roll-up antenna from our store. No cell service. No Wi-Fi. Just radio waves and a plan and tools that works. 💬 APRS isn’t just a GPS tool—it’s a true messaging system for real-world preparedness. I can send texts, share location, and stay connected—even across state lines. @hamradio360 @familyradioguy When the grid fails, this setup still works. 📍 From the backwoods to back home, your location shouldn’t isolate you. Store Link in Bio #preparedness #hamradio #aprs #familycomms #griddown #btechuvpro #wilcomantenna #btechradio #emergencycommunications #offgridready
#Proactive Vs Retroactive Interference Reel by @insightforge.ai - The Pearson correlation coefficient (r) is a statistical metric used to measure how strongly and in what direction two continuous variables are linear
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@insightforge.ai
The Pearson correlation coefficient (r) is a statistical metric used to measure how strongly and in what direction two continuous variables are linearly related. Its value ranges from -1 to 1, where: +1 indicates a perfect positive linear relationship, -1 indicates a perfect negative linear relationship, and 0 means there’s no linear relationship between the variables. In general, values closer to ±1 signify a stronger correlation, while those near 0 suggest a weak or negligible relationship. A positive correlation means both variables tend to increase together, whereas a negative correlation means one increases as the other decreases. The coefficient of determination (r²) is simply the square of the correlation coefficient. It tells us how much of the variation in one variable can be explained by its linear relationship with the other. For instance, if r = 0.8, then r² = 0.64, meaning 64% of the variance in one variable is explained by the other. C: 3 Minute Data Science #machinelearning #deeplearning #statistics #math #mathematics #computerscience #datascience #AI #education #science #dataanalysis #learning
#Proactive Vs Retroactive Interference Reel by @victoriaporozova (verified account) - BH Information Paradox solved via ER = EPR ⠀ What happens to information that falls into a black hole? In classical physics, it's lost forever. Anythi
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@victoriaporozova
BH Information Paradox solved via ER = EPR ⠀ What happens to information that falls into a black hole? In classical physics, it’s lost forever. Anything crossing the event horizon becomes inaccessible. This leads to the black hole information paradox, as quantum mechanics insists that information cannot be destroyed—it must be preserved. ⠀ Quantum Mechanics to the Rescue Hawking radiation suggests black holes emit energy as particle pairs: one escapes, the other falls inward. This radiation seems random and thermal, carrying no information about the black hole’s contents. But if information is truly lost, it violates quantum mechanics’ principle of unitarity. ⠀ The ER = EPR conjecture proposes a solution. It states that each particle emitted by the black hole is quantum-entangled with its internal contents, connected by mini-wormholes. These wormholes, though non-traversable, create a web linking the inside and outside of the black hole. ⠀ Mini-Wormholes and Information Recovery Through entanglement, the information falling into the black hole isn’t destroyed but encoded in quantum correlations. As the black hole evaporates, these entangled particles can theoretically reassemble, allowing the lost information to be retrieved and preserving unitarity. ⠀ Why It Matters ER = EPR not only resolves the paradox but also reveals that quantum entanglement might be the foundation of spacetime itself. By bridging quantum mechanics and general relativity, it reshapes our understanding of black holes and the universe. ⠀ Could ER = EPR redefine physics? Share your thoughts below! ⬇️ Do you like reels about Black holes? #physics #fyp #science #quantum #hawking #BlackHoles #QuantumPhysics #GeneralRelativity #HawkingRadiation #EventHorizon #Astrophysics #QuantumGravity #Einstein #ScienceExploration #theoreticalphysics #theoreticalphysicist #victoriaporozova #vquantpost

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