From 7e61dd7d2f844cece5f8c89d1def02b46563aad9 Mon Sep 17 00:00:00 2001 From: Ed_ Date: Sun, 21 Jun 2026 23:54:17 -0400 Subject: [PATCH] conductor(brain_counterintuitive): Phase 3 OCR - 91 frames OCR'd via winsdk in 14.7s --- .../artifacts/ocr.md | 1290 +++++++++++++++++ .../artifacts/phase2.log | 2 + .../artifacts/phase3.log | 2 + 3 files changed, 1294 insertions(+) create mode 100644 conductor/tracks/video_analysis_brain_counterintuitive_20260621/artifacts/ocr.md create mode 100644 conductor/tracks/video_analysis_brain_counterintuitive_20260621/artifacts/phase2.log create mode 100644 conductor/tracks/video_analysis_brain_counterintuitive_20260621/artifacts/phase3.log diff --git a/conductor/tracks/video_analysis_brain_counterintuitive_20260621/artifacts/ocr.md b/conductor/tracks/video_analysis_brain_counterintuitive_20260621/artifacts/ocr.md new file mode 100644 index 00000000..77f814f9 --- /dev/null +++ b/conductor/tracks/video_analysis_brain_counterintuitive_20260621/artifacts/ocr.md @@ -0,0 +1,1290 @@ +# OCR Results + +## frame_00001.jpg + +``` +(no text extracted) +``` + +## frame_00002.jpg + +``` +(no text extracted) +``` + +## frame_00003.jpg + +``` +(no text extracted) +``` + +## frame_00004.jpg + +``` +(no text extracted) +``` + +## frame_00005.jpg + +``` +(no text extracted) +``` + +## frame_00006.jpg + +``` +(no text extracted) +``` + +## frame_00007.jpg + +``` +(no text extracted) +``` + +## frame_00008.jpg + +``` +(no text extracted) +``` + +## frame_00009.jpg + +``` +Autonomous +Pattern Generation +``` + +## frame_00010.jpg + +``` +Autonomous +Yattern Generation n +``` + +## frame_00011.jpg + +``` +(no text extracted) +``` + +## frame_00012.jpg + +``` +(no text extracted) +``` + +## frame_00013.jpg + +``` +(no text extracted) +``` + +## frame_00015.jpg + +``` +(no text extracted) +``` + +## frame_00016.jpg + +``` +(no text extracted) +``` + +## frame_00017.jpg + +``` +(no text extracted) +``` + +## frame_00018.jpg + +``` +(no text extracted) +``` + +## frame_00019.jpg + +``` +(no text extracted) +``` + +## frame_00020.jpg + +``` +(no text extracted) +``` + +## frame_00021.jpg + +``` +(no text extracted) +``` + +## frame_00022.jpg + +``` +creates +``` + +## frame_00023.jpg + +``` +(no text extracted) +``` + +## frame_00024.jpg + +``` +(no text extracted) +``` + +## frame_00025.jpg + +``` +(no text extracted) +``` + +## frame_00026.jpg + +``` +(no text extracted) +``` + +## frame_00027.jpg + +``` +Network activity +``` + +## frame_00028.jpg + +``` +(no text extracted) +``` + +## frame_00029.jpg + +``` +(no text extracted) +``` + +## frame_00030.jpg + +``` +(no text extracted) +``` + +## frame_00031.jpg + +``` +(no text extracted) +``` + +## frame_00032.jpg + +``` +zlt) +``` + +## frame_00034.jpg + +``` +(no text extracted) +``` + +## frame_00035.jpg + +``` +mil +``` + +## frame_00036.jpg + +``` +(no text extracted) +``` + +## frame_00037.jpg + +``` +(no text extracted) +``` + +## frame_00038.jpg + +``` +Sponsored segment +nAlNS +Jeff Hawkins +``` + +## frame_00039.jpg + +``` +Sponsored segmen +• ILI +``` + +## frame_00041.jpg + +``` +Sponsored segment +``` + +## frame_00043.jpg + +``` +eDiscover- +--9Æ'GUO,.ÆOGY +(6) Podcasts-- +Libra; ; +A Thousand EBrains +Bv Jeff Hawkins +Continueeading +QL4udio avauabLRw. +Install the ADD +Google Play +BRAINS +Abou1500k +Ylodernrhnolo€aologäul pogræss is ablaze ithftlthesmtial of artifitifiéiialintdliéænce„ bwtvt Nill dönt tut1VVly undQdrstai +in+lliee.gemævwnks. cæqaSde ca$lhurnan +could use that knowledge to create even more powerful and useful-Q.I +'ITILdiÄA1'rusata presents a theory of intelligence rooted in how each component of +the brain creates mental models and makes predictions, just as the bralh aöes as a wholé. HäwKiris IS Ktiown Tor rilS +``` + +## frame_00044.jpg + +``` +wit awklnss characterization t at these co umns are the most aslC buildin I c so the +cerebral cortex. HoweVer, there IS still some debate about what actually constitutes a cortical +column. Since the term's introduction, its use hasn't been consistent in scientific literature, +Back to Books +sometimes referring to arrangements of nerve cells, and sometimes referring to other brain +features. It's also unclear how many cells they contain and how much they vary in design +throughout the brain.) +Within a cortical olumn, neurons receiv input through their dendrites—the finger-like +e the points at which nerve cells +extensions ont e n +connect. certain inputs and react when inputs differ from their +expectations. Hawkins explains that when multiple neurons in a cortical column receive the +BRAINS +same unexpected input, they "fire" as one, sending signali2!o other columns throughout the +Jeff Hawkins +brain. Since each neuron receives inputs from thousands of synapses, a single cortical column +can process hundreds of inputs, make predictions, and generate responses at the same time. +Two Nerve Cells (Neurons) +Cell Nucleus +Synapse +About Book +Install the App +Google Play +Download on the +App Store +Modern technological progress is ab@9 with the potential of artificial qelligence, but we still don't fully understand +how natural, human intelligence works. If we could crack the code of human cognition, many scientists believe we +could use that knowledge to create even more powerful and useful Al. +``` + +## frame_00045.jpg + +``` +cerebral cortex. However, there is still some debate about what actually constitutes a cortical +column. Since the term's introduction, its use hasn't been consistent in scientific literature, +sometimes referring to arrangements of nerve cells, and sometimes referring to other brain +features. It's also unclear how many cells they contain and how much they vary in design +throughout the brain.) +Within a cortical column, neurons receive input through their dendrites—the finger-like +extensions on the end of each nerve cell—and synapses—the points at which nerve cells +connect. Neurons learn to "predict" certain inputs and react when inputs differ from their +expectations. Hawkins explains that when multiple neurons in a cortical column receive the +same unexpected input, they "fire" as one, sending signals to other columns throughout the +brain. Since each neuron receives inputs from thousands of synapses, a single cortical column +can process hundreds of inputs, make predictions, and generate responses at the same time. +Two Nerve Cells (Neurons) +Cell Nucleus +Synapse +naao +``` + +## frame_00046.jpg + +``` +vvltrun a cortical column, neurons receive Input tnrougn tnelr aenarltes—tne tinger-11Ke +extensions on the end of each nerve cell—and synapses—the points at which nerve cells +connect. Neurons learn to "predict" certain inputs and react when inputs differ from their +expectations. Hawkins explains that when multiple neurons in a cortical column receive the +same unexpected input, they "fire" as one, sending signals to other columns throughout the +brain. Since each neuron receives inputs from thousands of synapses, a single cortical column +can process hundreds of inputs, make predictions, and generate responses at the same time. +Two Nerve Cells (Neurons) +Cell Nucleus +Synapse +(Shortform note: At the time of Hawkins's book's publication, neuroscience studies revealed +``` + +## frame_00047.jpg + +``` +Cell Nucleus +Synapse +(Shortform note: At the time of Hawkins's book's publication, neuroscience studies revealed +more about the mechanism by which individual neurons learn to predict the inputs they +eceive. In essence, each neuron tries to maximize its impact on other neurons while +minimizing its own energy consumption. In terms of biochemical efficiency, each neuron aims +to minimize the difference between its actual activity and its predicted activity. When the +actual amount of future activity differs from its prediction, a neuron updates its synaptic +connections to improve its predictions for similar inputs. By continuously updating their input +predictions, neurons become better at anticipating future activity patterns and reducing their +overall energy use.) +Models in the Mind +``` + +## frame_00048.jpg + +``` +0000 +(Shortform note: At the time of Hawkins's book's publication, neuroscience studies reveale +more about the mechanism by which individual neurons learn to predict the inputs they +receive. In essence, each neuron tries to maximize its impact on other neurons while +minimizing its own energy consumption. In terms of biochemical efficiency, each neuron aims +to minimize the difference between its actual activity and its predicted activity When the +actual amount of future activity differs from its prediction, a neuron updates its synaptic +connections to improve its predictions for similar inputs. By continuously updating their input +predictions, neurons become better at anticipating future activity patterns and reducing their +overall energy use.) +Models in the Mind +However many inputs they learn, no single neuron can create what we'd consider a coherent +``` + +## frame_00049.jpg + +``` +(Shortform note: At the time of Hawkins's book's publication, neuroscience studies revealed +more about the mechanism by which individual neurons learn to predict the inputs they +receive. In essence, each neuron tries to maximize its impact on other neurons while +minimizing its own energy consumption. In terms of biochemical efficiency, each neuron aims +to minimize the difference between its actual activity and its predicted activity When the +actual amount of future activity differs from its prediction, a neuron updates its synaptic +connections to improve its predictions for similar inputs. By continuously updating their input +predictions, neurons become better at anticipating future activity patterns and reducing their +overall energy use.) +Models in the Mind +However many inputs they learn, no single neuron can create what we'd consider a coherent +thought. That's why Hawkins asserts that clusters of neurons with thousands of connections are +f1 111" •r enneae generate reactions. Working +``` + +## frame_00050.jpg + +``` +(Shortform note: At the time of Hawkins's book's publication, neuroscience studies revealed +more about the mechanism by which individual neurons learn to predict the inputs the} +receive. In essence, each neuron tries to maximize its impact on other neurons while +minimizing its own energy consumption. In terms of biochemical efficiency, each neuron aims +to minimize the difference between its actual activity and its predicted activity. When the +actual amount of future activity differs from its prediction, a neuron updates its synaptic +connections to improve its predictions for similar inputs. By continuously updating their input +predictions, neurons become better at anticipating future activity patterns and reducing their +overall energy use.) +Models in the Mind +However many inputs they learn, no single neuron can create what we'd consider a coherent +thought. That's why Hawkins asserts that clusters of neurons with thousands of connections are +needed to fully interpret your senses and generate your mind and body's reactions. Working +te models ofvour environment. decide what to do and +``` + +## frame_00051.jpg + +``` +(Shortform note: At the time of Hawkins's book's publication, neuroscience studies revealed +more about the mechanism by which individual neurons learn to predict the inputs they +receive. In essence, each neuron tries to maximize its impact on other neurons while +minimizing its own energy consumption. In terms of biochemical efficiency, each neuron aims +to minimize the difference between its actual activity and its predicted activity. When the +actual amount of future activity differs from its prediction, a neuron updates its synaptic +connections to improve its predictions for similar inputs. By continuously updating their input +predictions, neurons become better at anticipating future activity patterns and reducing their +overall energy use.) +Models in the Mind +However many inputs they learn, no single neuron can create what we'd consider a coherent +thought. That's why Hawkins asserts that clusters of neurons with thousands of connections are +needed to fully interpret your senses and generate your mind and body's reactions. Working +together, these clusters of neurons create models ofyour environment, decide what to do and +``` + +## frame_00052.jpg + +``` +(Shortform note: At the time of Hawkins's book's publication, neuroscience studies revealed +more about the mechanism by which individual neurons learn to predict the inputs they +receive. In essence, each neuron tries to maximize its impact on other neurons while +minimizing its own energy consumption. In terms of biochemical efficiency, each neuron aims +to minimize the difference between its actual activity and its predicted activity. When the +actual amount of future activity differs from its prediction, a neuron updates its synaptic +connections to improve its predictions for similar inputs. By continuously updating their input +predictions, neurons become better at anticipating future activity patterns and reducing their +overall energy use.) +Models in the Mind +However many inputs they learn, no single neuron can create what we'd consider a coherent +thought. That's why Hawkins asserts that clusters of neurons with thousands of connections are +needed to fully interpret your senses and generate your mind and body's reactions. Working +together, these clusters of neurons create models of your environment, decide what to do and +``` + +## frame_00053.jpg + +``` +(Shortform note: At the time of Hawkins's book's publication, neuroscience studies revealed +more about the mechanism by which individual neurons learn to predict the inputs they +receive. In essence, each neuron tries to maximize its impact on other neurons while +minimizing its own energy consumption. In terms of biochemical efficiency, each neuron aims +to minimize the difference between its actual activity and its predicted activity. When the +actual amount of future activity differs from its prediction, a neuron updates its synaptic +connections to improve its predictions for similar inputs. By continuously updating their input +predictions, neurons become better at anticipating future activity patterns and reducing their +overall energy use.) +Models in the Mind +However many inputs they learn, no single neuron can create what we'd consider a coherent +thought. That's why Hawkins asserts that clusters of neurons with thousands of connections are +needed to fully interpret your senses and generate your mind and body's reactions. Working +together, these clusters of neurons create models ofyour environment, decide what to do and +more information about the world when your current +``` + +## frame_00054.jpg + +``` +(Shortform note: At the time of Hawkins's book's publication, neuroscience studies reveale +more about the mechanism by which individual neurons learn to predict the inputs they +receive. In essence, each neuron tries to maximize its impact on other neurons while +minimizing its own energy consumption. In terms of biochemical efficiency, each neuron aims +to minimize the difference between its actual activity and its predicted activity When the +actual amount of future activity differs from its prediction, a neuron updates its synaptic +connections to improve its predictions for similar inputs. By continuously updating their input +predictions, neurons become better at anticipating future activity patterns and reducing their +overall energy use.) +Models in the Mind +However many inputs they learn, no single neuron can create what we'd consider a coherent +thought. That's why Hawkins asserts that clusters of neurons with thousands of connections are +needed to fully interpret your senses and generate your mind and body's reactions. Working +together, these clusters of neurons create models of your environment, decide what to do and +think based on those models, and learn more information about the world when your current +models prove insufficient. +``` + +## frame_00055.jpg + +``` +(Shortform note: At the time of Hawkins's book's publication, neuroscience studies revealed +more about the mechanism bywhich individual neurons learn to predict the inputs the} +receive. In essence, each neuron tries to maximize its impact on other neurons while +minimizing its own energy consumption. In terms of biochemical efficiency, each neuron aims +to minimize the difference between its actual activity and its predicted activity. When the +actual amount of future activity differs from its prediction, a neuron updates its synaptic +connections to improve its predictions for similar inputs. By continuously updating their input +predictions, neurons become better at anticipating future activity patterns and reducing their +overall energy use.) +Models in the Mind +However many inputs they learn, no single neuron can create what we'd consider a coherent +thought. That's why Hawkins asserts that clusters of neurons with thousands of connections are +needed to fully interpret your senses and generate your mind and body's reactions. Working +together, these clusters of neurons create models ofyour environment, decide what to do and +think based on those models, and learn more information about the world when your current +models prove insufficient. +ictions, cortical columns model objects and their +``` + +## frame_00059.jpg + +``` +(Shortform note: At the time of Hawkins's book's publication, neuroscience studies reveale +more about the mechanism by which individual neurons learn to predict the inputs they +receive. In essence, each neuron tries to maximize its impact on other neurons while +minimizing its own energy consumption. In terms of biochemical efficiency, each neuron aims +to minimize the difference between its actual activity and its predicted activity When the +actual amount of future activity differs from its prediction, a neuron updates its synaptic +connections to improve its predictions for similar inputs. By continuously updating their input +predictions, neurons become better at anticipating future activity patterns and reducing their +overall energy use.) +Models in the Mind +However many inputs they learn, no single neuron can create what we'd consider a coherent +thought. That's why Hawkins asserts that clusters of neurons with thousands of connections are +needed to fully interpret your senses and generate your mind and body's reactions. Working +together, these clusters of neurons create models ofyour environment, decide what to do and +think based on those models, and learn more information about the world when your current +models prove insufficient. +Hawkins suggests that to make accurate predictions, cortical columns model objects and their +noeitione in three-dimeneional ueinø reference frames, which can be thought Of like the +``` + +## frame_00063.jpg + +``` +(Shortform note: At the time of Hawkins's book's publication, neuroscience studies revealed +more about the mechanism by which individual neurons learn to predict the inputs they +receive. In essence, each neuron tries to maximize its impact on other neurons while +minimizing its own energy consumption. In terms of biochemical efficiency, each neuron aims +to minimize the difference between its actual activity and its predicted activity. When the +actual amount of future activity differs from its prediction, a neuron updates its synaptic +connections to improve its predictions for similar inputs. By continuously updating their input +predictions, neurons become better at anticipating future activity patterns and reducing their +overall energy use.) +Models in the Mind +However many inputs they learn, no single neuron can create what we'd consider a coherent +thought. That's why Hawkins asserts that clusters of neurons with thousands of connections are +needed to fully interpret your senses and generate your mind and body's reactions. Working +together, these clusters of neurons create models ofyour environment, decide what to do and +think based on those models, and learn more information about the world when your current +models prove insufficient. +Hawkins suggests that to make accurate predictions, cortical columns model objects and their +positions in three-dimensional space using reference frames, which can be thought of like the +``` + +## frame_00070.jpg + +``` +(Shortform note: At the time of Hawkins's book's publication, neuroscience studies revealed +more about the mechanism by which individual neurons learn to predict the inputs they +receive. In essence, each neuron tries to maximize its impact on other neurons while +minimizing its own energy consumption. In terms of biochemical efficiency, each neuron aims +to minimize the difference between its actual activity and its predicted activity. When the +actual amount of future activity differs from its prediction, a neuron updates its synaptic +connections to improve its predictions for similar inputs. By continuously updating their input +predictions, neurons become better at anticipating future activity patterns and reducing their +overall energy use.) +Models in the Mind +However many inputs they learn, no single neuron can create what we'd consider a coherent +thought. That's why Hawkins asserts that clusters of neurons with thousands of connections are +needed to fully interpret your senses and generate your mind and body's reactions. Working +together, these clusters of neurons create models ofyour environment, decide what to do and +think based on those models, and learn more information about the world when your current +models prove insufficient. +Hawkins suggests that to make accurate predictions, cortical columns model objects and their +positions in three-dimensional space using reference frames, which can be thought of like the +grid lines on a map. His research shows that to create reference frames, neurons must be +connected to both sensory input and motor output—it isn't enough to see the world; your brain +``` + +## frame_00073.jpg + +``` +(Shortform note: At the time of Hawkins's book's publication, neuroscience studies revealed +ore about the mechanism bywhich individual neurons learn to predict the inputs the} +receive. In essence, each neuron tries to maximize its impact on other neurons while +minimizing its own energy consumption. In terms of biochemical efficiency, each neuron aims +to minimize the difference between its actual activity and its predicted activity. When the +actual amount of future activity differs from its prediction, a neuron updates its synaptic +connections to improve its predictions for similar inputs. By continuously updating their input +predictions, neurons become better at anticipating future activity patterns and reducing their +overall energy use.) +Models in the Mind +However many inputs they learn, no single neuron can create what we'd consider a coherent +thought. That's why Hawkins asserts that clusters of neurons with thousands of connections are +needed to fully interpret your senses and generate your mind and body's reactions. Working +together, these clusters of neurons create models ofyour environment, decide what to do and +think based on those models, and learn more information about the world when your current +models prove insufficient. +Hawkins suggests that to make accurate predictions, cortical columns model objects and their +positions in three-dimensional space using reference frames, which can be thought of like the +grid lines on a map. His research shows that to create reference frames, neurons must be +connected to both sensory input and motor output—it isn't enough to see the world; your brain +must be able to move through it. Different layers within a cortical column specialize in +``` + +## frame_00080.jpg + +``` +(Shortform note: At the time of Hawkins's book's publication, neuroscience studies reveale +more about the mechanism bywhich individual neurons learn to predict the inputs they +receive. In essence, each neuron tries to maximize its impact on other neurons while +minimizing its own energy consumption. In terms of biochemical efficiency, each neuron aims +to minimize the difference between its actual activity and its predicted activity. When the +actual amount of future activity differs from its prediction, a neuron updates its synaptic +connections to improve its predictions for similar inputs. By continuously updating their input +predictions, neurons become better at anticipating future activity patterns and reducing their +overall energy use.) +Models in the Mind +However many inputs they learn, no single neuron can create what we'd consider a coherent +thought. That's why Hawkins asserts that clusters of neurons with thousands of connections are +needed to fully interpret your senses and generate your mind and body's reactions. Working +together, these clusters of neurons create models ofyour environment, decide what to do and +think based on those models, and learn more information about the world when your current +models prove insufficient. +Hawkins suggests that to make accurate predictions, cortical columns model objects and their +positions in three-dimensional space using reference frames, which can be thought of like the +grid lines on a map. His research shows that to create reference frames, neurons must be +connected to both sensory input and motor output—it isn't enough to see the world; your brain +must be able to move through it. Different layers within a cortical column specialize in +modeling objects and their positions separately—some neurons learn the shape of an object, +``` + +## frame_00082.jpg + +``` +(Shortform note: At the time of Hawkins's book's publication, neuroscience studies revealed +more about the mechanism by which individual neurons learn to predict the inputs they +receive. In essence, each neuron tries to maximize its impact on other neurons while +minimizing its own energy consumption. In terms of biochemical efficiency, each neuron aims +to minimize the difference between its actual activity and its predicted activity When the +actual amount of future activity differs from its prediction, a neuron updates its synaptic +connections to improve its predictions for similar inputs. By continuously updating their input +predictions, neurons become better at anticipating future activity patterns and reducing their +overall energy use.) +Models in the Mind +However many inputs they learn, no single neuron can create what we'd consider a coherent +thought. That's why Hawkins asserts that clusters of neurons with thousands of connections are +needed to fully interpret your senses and generate your mind and body's reactions. Working +together, these clusters of neurons create models ofyour environment, decide what to do and +think based on those models, and learn more information about the world when your current +models prove insufficient. +Hawkins suggests that to make accurate predictions, cortical columns model objects and their +positions in three-dimensional space using reference frames, which can be thought of like the +grid lines on a map. His research shows that to create reference frames, neurons must be +connected to both sensory input and motor output—it isn't enough to see the world; your brain +must be able to move through it. Different layers within a cortical column specialize in +modeling objects and their positions separately—some neurons learn the shape of an object, +``` + +## frame_00083.jpg + +``` +SHORTFORM +The +Technological +Republic +Alexander C. Karp and +Nicholas W. Zamiska +POLITICS +The Technological +Republic +By Alexander C. Karp and +Nicholas W. Zamiska +Superagency +Reid Hoffman +and Greg Beato +SOCIETY/CULTURE +Superagency +@ Discover +SALES +Books +THE +Al EDGE +Jeb Blount and +Anthony Iannarino +Articles +Q Podcasts +Nicholas Carr +Superbloom +SOCIETY/CULTURE +Superbloom +By Nicholas Carr +SOURCE +CODE +Bill Gates +BIOGRAPHY/MEMOIR +Source Code +My Library +a +a +Q Search +How to +Create a +Mind +@000 +Ray Kurzweil +PSYCHOLOGY +How to Create a Mind +By Ray Kurzweil +IRREPLACEABLE +Pascal Bornet +CAREER/SUCCESS +Irreplaceable +Bv Pascal Bornet +8 +a +The Al Edge +By Jeb Blount and Anthony +Iannarino +The +Thinking +Machine +Stephen Witt +BIOGRAPHY/MEMOIR +The Thinking Machine +``` + +## frame_00084.jpg + +``` +SHORTFORM +SOCIETY/CULTURE +Superagency +By Reid Hoffman and Greg +Beato +POLITICS +Race After Technology +By Ruha Benjamin +Nexus +@ Discover +Books +Articles +Podcasts +BIOGRAPHY/MEMOIR +Source Code +By Bill Gates +CAREER/SUCCESS +My Library +a +a +Q Search +CAREER/SUCCESS +Irreplaceable +By Pascal Bornet +SCIENCE +Proust and the Squid +By Maryanne Wolf +IRRESISTIBLE +8 +a +a +BIOGRAPHY/MEMOIR +The Thinking Machine +By Stephen Witt +BIOGRAPHY/MEMOIR +Careless People +By Sarah Wynn-Williams +Gloria Mark +Attention +Span +6) +The ChatGPT Millionaire +By Neil Dagger +ATHOUSAND +BRAINS +``` + +## frame_00085.jpg + +``` +SHORTFORM +POLITICS +Race After Technology +By Ruha Benjamin +SOCIETY/CULTURE +Nexus +By Yuval Noah Harari +Steve Krug +@ Discover +BIOGRAPHY/MEMOIR +Careless People +By Sarah Wynn-Williams +PRODUCTIVITY +Attention Span +By Gloria Mark +The +Articles +Q) Podcasts +CAREER/SUCCESS +My Library +a +Q Search +SCIENCE +Proust and the Squid +By Maryanne Wolf +IRRESISTIBLE +Adam Alter +HEALTH +Irresistible +By Adam Alter +Mo Gawdat +8 +a +The ChatGPT Millionaire +By Neil Dagger +PSYCHOLOGY +A Thousand Brains +By Jeff Hawkins +Marty Cagan +and Chris Jones +a +``` + +## frame_00086.jpg + +``` +SHORTFORM +Race After Technology +By Ruha Benjamin +Nexus +Yuval Noah Harari +SOCIETY/CULTURE +Nexus +By Yuval Noah Harari +Steve Krug +DON'T +MAKE ME +THINK +@ Discover +Books +B Articles +Q Podcasts +My Library +Q Search +Proust and the Squid +By Maryanne Wolf +IRRESISTIBLE +Adam Alter +HEALTH +Irresistible +By Adam Alter +Mo Gawdat +Scary +Smart +8 +a +Careless People +By Sarah Wynn-Williams +Gloria Mark +Attention +Span +PRODUCTIVITY +Attention Span +By Gloria Mark +The +Shallows +Nicholas Carr +The ChatGPT Millionaire +By Neil Dagger +ATHOUSAND +BRAINS +Jeff Hawkins +PSYCHOLOGY +A Thousand Brains +By Jeff Hawkins +Marty Cagan +and Chris Jones +EMPOWERED +a +``` + +## frame_00087.jpg + +``` +nature communications +Explore content v About the journal v Publish with us v +nature > nature communications > perspectives > article +Perspective Open access I Published: 06 March 2024 +Emerging opportunities and challenges for the future +ofreservoir computing +Min Yan, Can Huang E, Peter Bienstman, Peter Tino, Wei Lin & Jie Sun E +Nature Communications 15, Article number: 2056 (2024) Cite this article +70k Accesses 332 Citations 18 Altmetric Metrics +An Author Correction +View all journa' +Sign u +Download PDF +Associated cont +Collection +Neuromorphic Har +2024 +Focus +AI and machine lea +SHORTFORM @ fiJ +Reservoir computing (RC) is a computational +x +o +Download PDF +to this article was published on 18 November 2024 +O This article has been updated +Abstract +Reservoir computing originates in the early 2000s, the core idea being to utilize dynamical +systems as reservoirs (nonlinear generalizations of standard bases) to adaptively learn +spatiotemporal features and hidden patterns in complex time series. Shown to have the +potential of achieving higher-precision prediction in chaotic systems, those pioneering works +led to a great amount of interest and follow-ups in the community of nonlinear dynamics and +Sections +Abstract +Introduction +Figu +Theory and algorithm +Physical design of RC +Application benchmar +Opportunities and tecl +Outlook +framework developed since the early 2000s that +leverages nonlinear dynamical systems as +reservoirs to learn complex spatiotemporal patterns, +showing promise in predicting chaotic systems with +high precision. +• RC architecture mimics brain-like processing with a +fixed input and nonlinear recurrent processing layer, +and a simple adaptive output layer, enabling fast +training and efficient signal processing. +Despite significant theoretical, algorithmic, and +experimental advances over two decades, RC has +yet to achieve widespread industrial adoption or +breakthrough applications beyond laboratory +settings. +• RC is particularly attractive for industry due to its +compact design, fast training, and potential for real- +time applications such as optical communication +distortion compensation, speech recognition, and +noise control. +The mathematical foundation of RC models the +system as a dynamical system with fixed internal +parameters and trainable output weights, often +optimized via regularized least squares to +approximate target time series. +Key design challenges include selecting optimal +• +internal coupling parameters to maintain rich, +bounded dynamics near the "edge of chaos," and +refining input, internal, and output layers to improve +have early access to a new product. Give us feedback on how to +``` + +## frame_00088.jpg + +``` +SHORTFORM @ +x +Publish with us v +)ectives > article +3 March 2024 +es and challenges for the future +)eter Tino, Wei Lin & Jie Sun E +2056 (2024) Cite this article +etric Metrics +lovember 2024 +Sign u +Download PDF +Associated cont +Collection +Neuromorphic Har +2024 +Focus +AI and machine lea +Sections +Abstract +Introduction +Figu +experimental advances over two decades, RC has +yet to achieve widespread industrial adoption or +breakthrough applications beyond laboratory +settings. +• RC is particularly attractive for industry due to its +compact design, fast training, and potential for real- +time applications such as optical communication +distortion compensation, speech recognition, and +noise control. +The mathematical foundation of RC models the +system as a dynamical system with fixed internal +parameters and trainable output weights, often +optimized via regularized least squares to +approximate target time series. +Key design challenges include selecting optimal +internal coupling parameters to maintain rich, +bounded dynamics near the "edge of chaos," and +refining input, internal, and output layers to improve +performance and data efficiency. +Recent advances explore structured and +hierarchical network designs, novel nonlinear +dynamics (e.g., optical, memristive, quantum +``` + +## frame_00089.jpg + +``` +(no text extracted) +``` + +## frame_00090.jpg + +``` +(no text extracted) +``` + +## frame_00091.jpg + +``` +Shane Parrish +CLEAR +öHJ'/K/t/O +``` + +## frame_00092.jpg + +``` +Shane Parrish +CLEAR +THINKING +``` + +## frame_00093.jpg + +``` +SHORTFORM +Our Content +Pricing About +Knowledge Hub +Login +10,000+ books, podcasts, & articles +5-day free trial +Read, Listen, Learn +Deeper than a summary. Faster than a book. +The key ideas, the context behind them, and enough depth to actually use what you learn. +Sign up for free +Start for free & cancel anytime. +DEEP +WORK +Cal Newport +The Gift +of Not +Belonging +Rami Kaminski +Better +Than +Before +Gretchen Rubin +Simon Squibb +What's Your +Dream? +THE +ART OF +D +ROBERT +GREENE +Winning +with People +NEVER +SPLIT THE +DIFFERENCE +CHRIS VOSS +PRINCIPLES +Shane Parrish +CLEAR +THINKING +Atomic +Habits +James Clear +THE 48 LAWS OF +POWER +ROBERT +GREENE +Sapiens +Yuval Noah Harari +THE +MILLION- +DOLLAR, +ONE- +PERSON +BUSINESS +Elaine Pofeldt +THE +LET THEM +THEORY +Stress Less, +Accomplish +More +AWAKEN +THE GIANT +WITHIN +TONY ROBBINS +STRONG +ROUND +Elastic +Habits +Stephen Guise +MARK MANSON +THE +SUBTLE +ART OF +NOT +GIVING +A F•CK +THINKI +FAST A +SLO +DANIE +KAHNE +Thi +s +Done +shortform.com/artem +``` + +## frame_00094.jpg + +``` +What if we embraced +the mess instead of +trying to tame it? +Herbert Jaeger +o oo +00 ooo +Wolfgang Maass +Reservoir Computing +``` + +## frame_00095.jpg + +``` +Reservoir C +``` + +## frame_00096.jpg + +``` +. 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