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The transcript discusses Pattern Recognition and Deduction HI (Human Intelligence in AI) with an AI-generated voice and subtitles. It presents a Pattern Set in which fruits provide magnesium, and a Deduction Path showing that these fruits contain magnesium. The fruits explicitly named as providing magnesium are figs, bananas, avocados, blackberries, raspberries, papayas, kiwifruits, and apricots. It notes that the Deduction source for pattern sets is to provide magnesium, and it references related pattern sets concerning the health benefits of a right amount of magnesium. The speaker argues that Pattern Recognition and Deduction HI will be a central and main paradigm in artificial intelligence because it does not depend on huge computing power and memory size as brute force AI does. This claim is illustrated with pattern sets in Connect Four. The transcript states that pattern sets will be the dominant structure to represent, store, recognize knowledge, and deduce new knowledge, i.e., new pattern sets, from existing knowledge, from existing pattern sets. As such, pattern sets are linked to each other by a deduction path, and possibly other link types. It is proposed that the uncensored, hyperlinked Internet and social media are very well suited to host, share, and collaborate inequality on common reusable pattern sets for people. In this view, pattern recognition and deduction with pattern sets is an attempt to simulate a more human and, as such, smarter form of modeling and reasoning than brute force AI. The transcript closes with “To be continued.” The source cited is tomie.org.

Pattern recognition and deduction are presented as central to human intelligence and artificial intelligence. The talk references pattern sets and specific notation for Connect Four scenarios, including pattern sets labeled as re one PPP, REO PP, and deduced from re one PPP. It describes a process where a winning move, denoted as REO of re one r e o p p, is identified, and after making this winning move, the pattern set specified under “deduced from pattern sets” harunder is created by following in reverse the deduction path described earlier. Key ideas include the notion that there are columns and patterns (p sets) that determine the winning sequence. A deduced pattern set, such as p set two (p set to a one re one PPP), is defined by a deduction path that considers all columns and the opponent’s possible disconnections on a depth measured with rio PPP. A condition is stated: there exists exactly one column with exactly one empty position that aligns with the REO position of re one re o p p. The claim is that all RE one re zero p p patterns involved are tied to specific columns that do not require a rewon pattern because playing the winning move REO transforms all involved rewon rezero p p patterns into rewon patterns. The text then mentions “pink call one p p p” in an all-columns pattern set for a winning move, with m moves, and indicates that every open column other than certain specific columns either closes or contains a rewon PPP. Consequently, an opponent’s move on any other open column would create a re OPPP that enables the player to win. An example is given for p sets three dot x dot y connects four and three moves, stating that no p sets one dot b dot w connects four and one move of the opponent may exist after the specified player’s move. The speaker asserts that pattern recognition and deduction, labeled as HI, will be a central paradigm in AI because it does not rely on enormous computing power or memory, unlike brute force methods. The idea is to simulate a more human and smarter form of modeling and reasoning rather than brute force. The talk closes with “To be continued,” and credits tumea.org as the source, followed by a request to like, follow, and share.

Pattern Recognition and Deduction HI, Human Intelligence in AI, AI generated Voice Christ and subtitles, Ecosystem Pattern Set, are sources for phosphorus extraction or recycling, Deduction path collection of sources for phosphorus p15 extraction or recycling. Deduced from pattern sets, sedimentary phosphate rocks are sources for phosphorus extraction. Igneous phosphate rocks are sources for phosphorus extraction. Agricultural runoffs are sources for phosphorus recycling. Animal droppings are sources for phosphorus recycling. Sewage streams are sources for phosphorus recycling. Household wastewater streams are sources for phosphorus recycling. Organic waste materials through composting are sources for phosphorus recycling. Crop residues through decomposition or tillage are sources for phosphorus recycling. Waste streams from industries using phosphorus, detergents, fertilizers are sources for phosphorus recycling. Related pattern sets with keyword phosphorus are health benefits of a right amount of phosphorus. Hold phosphorus related pattern sets with keyword extraction are sources for salt extraction. I think pattern sets will be a dominant structure to represent, store and recognize knowledge and deduce new knowledge, new pattern sets from existing knowledge from existing pattern sets. Thus pattern sets are linked to each other by deduction path in other link types and as such the uncensored hyperlinked Internet and social media are very well suited to host, share and collaborate in equality on common reusable pattern sets for people. Pattern set deduction does not depend on huge computing power and memory size as brute force AI does as is being demonstrated with pattern sets in Connect four. To be continued: source2mia.org. Please like, follow and share.

The speaker discusses pattern recognition and deduction as a central paradigm for artificial intelligence, describing a framework built around pattern sets and deduction paths in the game of Connect Four. The core idea is to use pattern recognition to identify a winning move by following a deduction path through various pattern sets, including re one PPP, re one REO PP, and deducing from re one PPP. The process begins with a winning move REO (re one r e o p p) and, after playing this move, the pattern set specified under deduced from pattern sets harunder is created by following the deduction path in reverse. Key components include: - Deduced from pattern sets p set to a one re one PPP deduction path, which considers all columns and the opponent’s discommission on depth of rio PPP. - A condition list states that there exists exactly one column with exactly one empty position that corresponds with the REO position of re one re o p p pattern sets. The pattern sets involve specific columns that do not need a rewon pattern because, if the winning move is played, REO, all involved rewon zero p p patterns transform into rewon patterns. - The description notes there are pink call one p p p in an all columns pattern set for winning and m moves; every other open column besides specific columns with other specific conditions has a rewon pattern. Consequently, any opponent move on any other open column creates a re OPPP, enabling the player to win. - After the winning move, no pattern set p set of the opponent may exist on the board that would imply a faster win for the opponent. If the player can choose more than one column to win, it is sufficient that no faster opponent win exists after the player’s move on one of those winning columns. - An example is given: for p sets three dot x dot y connects four and three moves, no p sets one dot b dot w connects four and one move of the opponent may exist after the specified player’s move. The speaker emphasizes that pattern recognition and deduction are seen as central to artificial intelligence, arguing that this approach does not depend on huge computing power and memory as brute force does. The concept aims to simulate a more human and smarter form of modeling and reasoning than brute force, attempting to emulate human reasoning. The talk ends with a note that it will continue, citing tumea.org, and a request to like, follow, and share.

Speaker 0 discusses pattern recognition and deduction as central to human intelligence, along with generated voice and subtitles. The ecosystem of “pattern set” sources is identified as sources for salt extraction. The deduction path involves the collection of sources for salt (sodium) extraction, deduced from pattern sets. Sources listed for salt extraction include seas, salt mines, salt surface deposits, salt lakes, salt pans, brine wells, and brine springs. Related pattern sets with the keyword sodium cover health aspects: health benefits of a right amount of sodium; provide sodium in fresh and processed seafoods; vegetables provide sodium; health damages of chronic excessive consumption of sodium; health damages of insufficient consumption of sodium. The speaker posits that pattern sets will be a dominant structure to represent, store, and recognize knowledge and to deduce new knowledge from existing pattern sets. Pattern sets are linked to each deduction path and other link types, and thus the uncensored hyperlinked Internet and social media are very well suited to host, share, and collaborate in equality on common reusable pattern sets knowledge for people. Pattern set deduction does not depend on huge computing power and memory size as brute force AI does, as is being demonstrated with pattern sets in connect four to be continued. A source is cited: you mere.org. The message ends with an instruction to “Please like, follow, and share.”

Phosphorus appears as a common element across a wide range of products and materials. The transcript outlines a pattern-based approach to knowledge, suggesting that many items “hold phosphorus” and thus rely on phosphorus in their production or composition. The list of phosphorus-containing categories includes: - Fertilizers for agriculture - Additives in the food and beverage industry - Various chemicals - Cleaning products - Flame retardants - Semiconductors - Solar cells - Some pharmaceuticals - Some steel and bronze - Some battery types - Explosives - Smoke bombs - Matches It also notes a related pattern set: “health benefits of a right amount of phosphorus.” A core idea presented is that pattern sets can serve as a dominant structure to represent, store, and recognize knowledge and to deduce new knowledge. Pattern sets are described as being linked to each other by a deduction path and other link types. The uncensored hyperlinked Internet and social media are characterized as well-suited to host, share, and collaborate in equality on common reusable pattern sets knowledge for people. The deduction process is described as not requiring huge computing power and memory, unlike brute-force AI. This is illustrated by a claim that pattern sets are demonstrated in Connect Four. The overarching theme is that new pattern sets can be created from existing knowledge and linked through deduction paths to expand understanding. The transcript ends with a continuation note and a brief, non-technical remark about pattern sets being a dominant structure for knowledge representation and discovery, followed by an indicator that there is more to come.

Speaker 0 discusses pattern recognition and deduction, AI-generated voice, and subtitles in an ecosystem. It then presents a sequence of health benefits attributed to Hawthorne, deduced from pattern sets: - good heart function is a health benefit of Hawthorne - vascular resistance reduction is a health benefit of Hawthorne - Improved blood circulation is a health benefit of Hawthorne - Blood pressure regulation is a health benefit of Hawthorne - Cholesterol regulation is a health benefit of Hawthorne - Vascular protection is a health benefit of Hawthorne - Protection against atherosclerosis is a health benefit of Hawthorne - Inflammation reduction is a health benefit of Hawthorne - Indigestion relief is a health benefit of Hawthorne - Metabolism regulation is a health benefit of Hawthorne - Neurotransmitters regulation is a health benefit of Hawthorne - Stress relief is a health benefit of Hawthorne - Anxiety relief is a health benefit of Hawthorne - Anti aging is a health benefit of Hawthorne The transcript notes that related pattern sets with keyword Hawthorne are provided by Hawthorne, and related pattern sets with keyword health discuss the health benefits of a right amount of magnesium, health benefits of a right amount of sodium, health damages of a chronic excessive consumption of sodium, health damages of an insufficient consumption of sodium, health benefits of a right amount of phosphorus, health damages of an excessive consumption of phosphorus, and health damages of an insufficient consumption of phosphorus. It mentions related pattern sets with keyword hawthorn on Deep CKI with Baidu chat to translate to English, including examples such as which animal species feed on Hawthorne, which bird species feed on Hawthorne, which nutrients are provided by Hawthorne, which minerals are provided by Hawthorne, and what are health benefits of Hawthorne. The speaker asserts that pattern sets will be a dominant structure to represent, store, and recognize knowledge and deduce new knowledge, including new pattern sets from existing knowledge. Pattern sets are linked to each other by deduction path and other link types, and uncensored hyperlinked Internet and social media are well suited to host, share, and collaborate in a quality on common reusable pattern sets knowledge for people. Pattern set deduction does not depend on huge computing power and memory size as brute force AI does, as is being demonstrated with pattern sets in Connect four to be continued. Source tumea.org.

Speaker 0: Pattern recognition and deduction HI. Human intelligence in AI. AI generated voice, DORIS, and subtitles. Ecosystem pattern set minerals are provided by figs. Deduction path. Collection of minerals and trace elements within figs. Deduced from pattern sets. Sodium Na, 11 is provided by figs. Magnesium Mg, 12 is provided by figs. Phosphorus P, 15 is provided by figs. Potassium K, 19 is provided by figs. Calcium California, 20 is provided by figs. Manganese Mn, 25 is provided by FIGs. Iron Fe, 26 is provided by FIGs. Nickel Ni, 28 is provided by FIGs. Copper Cu, 29 is provided by FIGs. Zinc Zn, 30 is provided by Figs. Strontium Sr, 38 is provided by Figs. Deduction source for pattern sets are provided by Figs. I think the concept of pattern recognition and deduction HI, human intelligence, will be a central and main paradigm in artificial intelligence because it does not depend on huge computing power and memory size as brute force AI does. As is being demonstrated with pattern sets in Connect Four, I also think pattern sets will be a dominant structure to represent, store, and recognize knowledge and deduce new knowledge. New pattern sets from existing knowledge. Existing pattern sets. Thus pattern sets are linked to each other by deduction path and possibly other link types and as such the uncensored hyperlink, Internet and social media are very well suited to host. Share and collaborate inequality on common reusable pattern sets knowledge for people. In fact, pattern recognition and deduction with pattern sets is an attempt to simulate a more human and as such smarter form of modeling and reasoning than brute force. And AI trying to do it the human way. To be continued, source tomiaorg. Please like, follow and share. Speaker 1: Pattern recognition and deduction HI, human intelligence in AI. AI generated voice Christ and subtitles, ecosystem pattern set feed on figs, deduction path, collection of orders, families, and species that feed on figs, Deduced from pattern sets, humans feed on figs, birds feed on figs, rodents feed on figs, insects feed on figs, bats feed on figs, primates feed on figs, civets feed on figs, elephants feed on figs, kangaroos feed on figs. I think the concept of pattern recognition deduction HI, human intelligence, will be a central and main paradigm in artificial intelligence because it does not depend on huge computing power and memory size as brute force AI does as is being demonstrated with pattern sets in Connect Four. I also think pattern sets will be a dominant structure to represent, store, and recognize knowledge and deduce new knowledge, new pattern sets from existing knowledge, existing pattern sets. Thus pattern sets are linked to each other by deduction path and possibly other link types and as such the uncensored hyperlinked Internet and social media are very well suited to host, share and collaborate in equality on common reusable pattern sets knowledge for people. In fact pattern recognition deduction with pattern sets is an attempt to simulate a more human and as such smarter form of modeling and reasoning than brute force and AI trying to do it the human way To be continued, sourceto mea.org. Please like, follow, and share. Speaker 2: Pattern recognition and deduction HI, human intelligence in my I generated voice Ethan and subtitles. Ecosystem pattern set are provided by figs deduction path, collection of nutrients and phytochemicals within figs. Deduced from pattern sets, dietary fibers are provided by figs, Vitamins are provided by figs. Minerals are provided by figs. Antioxidants are provided by figs. Natural sugars are provided by figs. Phenolic acids are provided by figs. Flavonoids are provided by figs. Carotenoids are provided by figs. Organic acids are provided by figs. I think the concept of pattern recognition and deduction HI, human intelligence, will be a central and main paradigm in artificial intelligence because it does not depend on huge computing power and memory size as brute force AI does as is being demonstrated with pattern sets in connect four. I also think pattern sets will be a dominant structure to represent, store, and recognize knowledge and deduce new knowledge, new pattern sets from existing knowledge, existing pattern sets. Thus pattern sets are linked to each other by deduction path and possibly other link types and as such the uncensored hyperlinked Internet and social media are very well suited to host, share, and collaborate inequality on common reusable pattern sets knowledge for people. In fact, pattern recognition and deduction with pattern sets is an attempt to simulate a more human and as such smarter form of modeling and reasoning than brute force, and I trying to do it the human way. To be continued, source to umia.org. Please like, follow, and share. Speaker 3: Pattern recognition and deduction HI, human intelligence in AI. AI generated voice Jessica and subtitles. Ecosystem pattern set birds feed on figs. Deduction path, collection of bird families, genera and species that feed on figs. Deduced from pattern sets, starlings feed on figs, blackbirds feed on figs, song thrushes feed on figs, wood pigeons feed on figs, jays feed on figs, house sparrows feed on figs, greenfinches feed on figs, fig birds feed on figs, Tucans feed on figs. Hornbills feed on figs. Pigeons feed on figs. Bowerbirds feed on figs. Crows feed on figs. I think the concept of pattern recognition and deduction HI, human intelligence, will be a central and main paradigm in artificial intelligence because it does not depend on huge computing power and memory size as brute force AI does as is being demonstrated with pattern sets in Connect four. I also think pattern sets will be a dominant structure to represent, store, and recognize knowledge and deduce new knowledge, new pattern sets from existing knowledge, existing pattern sets. Thus pattern sets are linked to each other by deduction path and possibly other link types. And as such, the uncensored hyperlinked Internet and social media are very well suited to host, share and collaborate in a quality on common reusable pattern sets knowledge for people. In fact, pattern recognition and deduction with pattern sets is an attempt to simulate a more human and as such smarter form of modeling and reasoning than brute force and AI trying to do it the human way. To be continued. Source tumia.org. Please like, follow, and share. Speaker 0: Pattern recognition and deduction HI. Health benefits of a right amount of magnesium are discussed within ecosystem pattern set. Deduction path. Collection of health benefits of a right amount of magnesium. Deduced from pattern sets. Good muscle function is a health benefit of a right amount of magnesium. Bone strength is a health benefit of a right amount of magnesium. The heart function is a health benefit of a right amount of magnesium. Blood pressure regulation is a health benefit of a right amount of magnesium. Relaxation is a health benefit of a right amount of Stress reduction is a health benefit of a right amount of magnesium. Sleep quality is a health benefit of a right amount of magnesium. Blood sugar regulation is a health benefit of a right amount of Magnesium. Inflammation reduction is a health benefit of a right amount of magnesium. Digestion support is a health benefit of a right amount of magnesium. Mental well-being is a health benefit of a right amount of magnesium. Migraine reduction is a health benefit of a right amount of magnesium. I think the concept of pattern recognition and deduction, HI. Human intelligence will be a central and main paradigm in artificial intelligence because it does not depend on huge computing power and memory size as brute force AI does. As is being demonstrated with pattern sets in Connect Four, I also think pattern sets will be a dominant structure to represent, store and recognize knowledge and deduce new knowledge. New pattern sets from existing knowledge. Existing pattern sets. Thus pattern sets are linked to each other by deduction path and possibly other link types and as such the uncensored hyperlink ad Internet and social media are very well suited to host. Share and collaborate inequality on common reusable pattern sets knowledge for people. In fact, pattern recognition and deduction with pattern sets is an attempt to simulate a more human and as such smarter form of modeling and reasoning than brute force.

Pattern recognition and deduction HI. Human intelligence in AI. AI generated voice, DORIS, and subtitles. Ecosystem pattern set minerals are provided by FIGs. Deduction path. Collection of minerals and trace elements within figs. Deduced from pattern sets. Sodium Na, 11 is provided by figs. Magnesium Mg, 12 is provided by figs. Phosphorus P, 15 is provided by figs. Potassium K, 19 is provided by figs. Calcium Ca, 20 is provided by figs. Manganese Mn, 25 is provided by FIGs. Iron Fe, 26 is provided by FIGs. Nickel Ni, 28 is provided by FIGs. Copper Cu, 29 is provided by FIGs. Zinc Zn, 30 is provided by FIGs. Strontium Sr, 38 is provided by FIGs. Deduction source for pattern sets are provided by FIGs. I think the concept of pattern recognition and deduction HI, human intelligence, will be a central and main paradigm in artificial intelligence because it does not depend on huge computing power and memory size as brute force AI does. As is being demonstrated with pattern sets in Connect four, I also think pattern sets will be a dominant structure to represent, store, and recognize knowledge and deduce new knowledge. New pattern sets from existing knowledge. Existing pattern sets. Thus, pattern sets are linked to each other by deduction path and possibly other link types and as such the uncensored hyperlink. Ed Internet and social media are very well suited to host. Share and collaborate inequality on common reusable pattern sets knowledge for people. In fact, pattern recognition and deduction with pattern sets is an attempt to simulate a more human and as such smarter form of modeling and reasoning than brute force. And AI trying to do it the human way. To be continued, source tumiyaorg. Please like, follow, and share.

The transcript discusses a formal framework for pattern recognition and deduction in the game of Connect Four, emphasizing a human-like reasoning approach over brute-force computation. It outlines a system of pattern sets and deduction paths used to identify winning moves and counter-moves. Key elements: - Pattern recognition and deduction are applied to Connect Four with a focus on identifying winning moves through a structured pattern set hierarchy. - Pattern sets are labeled (for example, re one PPP, re one REO PP, p set to a one, etc.), and a deduction path is derived from these sets. The path is followed in reverse to generate a pattern set that supports the winning move. - A winning move is denoted as REO (or REO PPP), and after playing this winning move, the pattern set deduced from the pattern sets harunder is produced by reversing the deduction path described earlier. - Deduced pattern sets (p set to a one, re one PPP) lead to a deduction path determined by all columns and the opponent’s possible responses (discommission) at depth rio PPP. - A condition is stated: there exists exactly one column with exactly one empty position that corresponds to the REO position of re one REO PPP. This column is pivotal because all rewon PPP patterns involved are specific columns that do not require a REWON pattern; if the winning move is played, all involved REWON rezero PPP patterns transform into REWON patterns. - The description mentions “pink call one PPP” in an all-columns pattern set for winning moves, with M moves. Most open columns, except the specific ones with additional conditions, are described as either closed or containing a rewon PPP. - Consequently, an opponent’s move on any other open column creates a re OPPP, enabling the current player to win. - After the winning move is played, no pattern set P set of the opponent should imply a faster win for the opponent. If multiple winning columns exist, it is sufficient that no faster opponent win exists after the move on one of those columns. - An example is given: for p sets three dot x dot y (connects four in three moves), no p sets one dot b dot w (connects four in one move by the opponent) may exist after the specified player’s move. - The broader concept presented is that pattern recognition and deduction represent a central paradigm in artificial intelligence because they do not depend on brute-force computing power or memory size; rather, they aim to model and simulate smarter human reasoning. - The speaker notes that pattern deduction attempts to simulate a more human and smarter form of modeling and reasoning than brute force, and signals that the discussion will continue. Note: Promotional requests at the end of the original transcript have been omitted.

Pattern recognition and deduction AI discuss pattern sets and their health benefits when phosphorus is consumed in the right amount. The health benefits listed for phosphorus include bone strength, teeth strength, cellular energy production, DNA and RNA formation, good tissue growth, good tissue repair, good acid-base balance, metabolism support, good muscle function, good nerve function, and good kidney function. The concept connects pattern sets with related keywords such as health benefits of a right amount of magnesium and health benefits of a right amount of sodium, as well as health damages of chronic excessive sodium consumption and health damages of insufficient sodium consumption. The speakers suggest that pattern sets will be a dominant structure to represent, store, and recognize knowledge, and to deduce new knowledge from existing pattern sets. Pattern sets are described as being linked to each other by deduction paths and other link types. The discussion posits that an uncensored hyperlinked Internet and social media are well suited to host, share, and collaborate on high-quality, common, reusable pattern sets knowledge. It is asserted that pattern set deduction does not depend on huge computing power and memory size as brute force AI does, with a reference example to Connect Four. The transcript ends with an indication that the topic will continue.

Speaker 0 discusses pattern recognition and deduction as a central AI paradigm that contrasts with brute-force computing. The talk uses Connect Four as the running example and introduces structured pattern sets and deduction paths. Key concepts: - Pattern sets and deduced patterns: A winning move REO PPP is identified within a pattern set. After playing this winning move, the pattern set specified under “deduced from pattern sets” is created by following the deduction path in reverse. - Notation and patterns: Pattern sets include re one PPP, re one REO PP, deduced from re one PPP. The deduction path applies to all columns and the opponent’s discommission on depth of rio PPP. - Column conditions for a unique winning move: The condition list for re one re zero pon topo fona states there exists exactly one column with exactly one empty position that corresponds with the REO position of re one REO PPP. All raises of re one re zero PPP patterns involve specific columns that do not need a REWON pattern because if the player plays the winning move REO, all involved REWON REZERO PPP patterns transform into REWON patterns. - Column status and opponent moves: There are “pink call one ppp” in an all-columns pattern set for winning and M moves; every open column besides specific columns with other conditions has a REWON pattern. Consequently, an opponent’s move on any other open column creates a REOPPP, enabling the player to win. - After a winning move: After the player’s winning move as specified by the winning move property, no pattern set p set of the opponent may exist on the board that implies a faster win for the opponent. If the player can choose more than one column to win, it is sufficient that no faster opponent win exists after the player’s move on one of those winning columns. - Example: For p sets three dot x dot y Connect Four and three moves, no p sets one dot b dot w Connect Four and one move of the opponent may exist after the specified player’s move. - Rationale and broader claim: The concept of pattern recognition and deduction is argued to be central in AI because it does not depend on huge computing power and memory as brute force does. Pattern deduction is presented as an attempt to simulate a more human and smarter form of modeling and reasoning than brute force, trying to do it the human way. - Source: tumea.org. Closing call to action: please like, follow, and share.

The transcript presents a series of discussions around pattern recognition and deduction as a central paradigm in artificial intelligence, illustrated through a Connect Four context. Each speaker outlines how specific pattern sets are defined, how deductions are made, and how these patterns guide winning moves in Connect Four in three moves. Key concepts across speakers: - Pattern recognition and deduction HI (human intelligence) is proposed as a less power-intensive alternative to brute-force AI, aiming to simulate human-like reasoning. - A “pattern set” consists of two patterns (often labeled with Re, PPP, PP, etc.) that share certain structural relationships. The patterns specify how pieces (Re) align in columns and rows to create potential winning configurations. - Deductions are described as “deduction paths” and “empty siding forks” (or similar fork structures) that emerge after a specified move, indicating a winning or faster-win opportunity without enabling an immediate counter-win by the opponent. - The core objective is to ensure that after a player executes a winning move, no pattern set (or faster win) exists for the opponent on the board. If multiple winning columns exist, it is sufficient that at least one avoids giving the opponent a faster win. - The pattern relationships are technical and involve columns sharing (or not sharing) the same column between elements of the two patterns, with terms like “rotatable empty position,” “shared column,” and “different siding columns” used to describe the configurations. - Several explicit examples are given (repeated across speakers) to illustrate how a player can force a win by selecting a particular column (or pattern element) that yields a “P Set” (e.g., P Set two s one, empty siding fork) or its variant, depending on the specific pattern pair. - Each speaker repeats the same overarching idea, with minor variations in the pattern lists (e.g., Re0PPP, Re0PPP, Re1RE0PP, etc.) and the deduction language (e.g., “disk omission/emission,” “vertical pattern,” “two pairs sharing a column,” etc.). - The existential claim is that pattern recognition and deduction could be central to AI because it does not rely on brute force and memory size, instead focusing on smarter modeling and reasoning. The discussions conclude with a cue to continuity and a call to viewers to like, follow, and share. Notable aspects: - The repeated framing of two-pattern sets and their columnar relationships as the basis for generating winning moves. - The emphasis on “no faster win for the opponent” after the player’s move as a crucial validity condition for the deduction. - The frequent use of Connect Four as a concrete testbed for illustrating pattern-based reasoning and the proposed paradigm shift in AI approaches.

Speaker 0: Pattern recognition and deduction HI. Human intelligence in AI. AI generated voice Byron and subtitles. Ecosystem pattern set are health benefits of a right amount of magnesium. Deduction path. Collection of health benefits of a right amount of magnesium. Deduced from pattern sets. Good muscle function is a health benefit of a right amount of magnesium. Bone strength is a health benefit of a right amount of magnesium. The heart function is a health benefit of a right amount of magnesium. Blood pressure regulation is a health benefit of a right amount of magnesium. Relaxation is a health benefit of a right amount of Stress reduction is a health benefit of a right amount of magnesium. Sleep quality is a health benefit of a right amount of Blood sugar regulation is a health benefit of a right amount of Inflammation reduction is a health benefit of magnesium. Digestion support is a health benefit of magnesium. Mental well-being is a health benefit of magnesium. Migraine reduction is a health benefit of a right amount of magnesium. I think the concept of pattern recognition and deduction, HI. Human intelligence will be a central and main paradigm in artificial intelligence because it does not depend on huge computing power and memory size as brute force AI does. As is being demonstrated with pattern sets in Connect four, I also think pattern sets will be a dominant structure to represent, store and recognize knowledge and deduce new knowledge. New pattern sets. From existing knowledge. Existing pattern sets. Thus pattern sets are linked to each other by deduction path and possibly other link types and as such the uncensored hyperlink. Ed Internet and social media are very well suited to host. Share and collaborate inequality on common reusable pattern sets knowledge for people. In fact, pattern recognition and deduction with pattern sets is an attempt to simulate a more human and as such smarter form of modeling and reasoning than brute force. And AI trying to do it the human way. To be continued. Source

Pattern Recognition and Deduction HI AI generated Voice David and Subtitles Ecosystem Pattern Set are health damages of an insufficient consumption of Phosphorus Deduction path: Collection of health damages of an insufficient consumption of phosphorus. Deduced from pattern sets: Bone weakness is a health damage of an insufficient consumption of phosphorus. Bone pain is a health damage of an insufficient consumption of phosphorus. Muscle weakness is a health damage of an insufficient consumption of phosphorus. Muscle pain is a health damage of an insufficient consumption of phosphorus. Respiratory muscle weakness is a health damage of an insufficient consumption of phosphorus. Impaired memory is a health damage of an insufficient consumption of phosphorus. Confusion is a health damage of an insufficient consumption of phosphorus. Irritability is a health damage of an insufficient consumption of phosphorus. Anxiety is a health damage of an insufficient consumption of phosphorus. Depression is a health damage of an insufficient consumption of phosphorus. Seizure is a health damage of an insufficient consumption of phosphorus. Coma is a health damage of an insufficient consumption of phosphorus. Impaired cell repair is a health damage of an insufficient consumption of phosphorus. Impaired cell growth is a health damage of an insufficient consumption of phosphorus. Impaired metabolism is a health damage of an insufficient consumption of phosphorus. Impaired growth in children is a health damage of an insufficient consumption of phosphorus. Appetite loss is a health damage of an insufficient consumption of phosphorus. Weight loss is a health damage of an insufficient consumption of phosphorus. Compromised immune function is a health damage of an insufficient consumption of phosphorus. Anaemia is a health damage of an insufficient consumption of phosphorus. Impaired kidney function is a health damage of an insufficient consumption of phosphorus. Related pattern sets with keyword Phosphorus, Our health benefits of a right amount of Phosphorus. Hold Phosphorus. Our sources for Phosphorus extraction or recycling. Provide Phosphorus. R health damages of an excessive consumption of Phosphorus R health benefits of a right amount of Sodium are health damages of a chronic excessive consumption of sodium are health damages of an insufficient consumption of sodium are health benefits of a right amount of phosphorus Our health damages of an excessive consumption of phosphorus. I think pattern sets will be a dominant structure to represent, store and recognize knowledge and deduce new knowledge new pattern sets, from existing knowledge, from existing pattern sets. Thus pattern sets are linked to each other by deduction path and other link types and as such the uncensored hyperlinked Internet and social media are very well suited to host, share and collaborate in equality on common reusable pattern sets knowledge for people. Pattern set deduction does not depend on huge computing power and memory size as brute force AI does, as is being demonstrated with pattern sets in Connect four. To be continued.

Pattern recognition and deduction HI, human intelligence in AI. AI-generated voice, subtitles. Ecosystem pattern set fed on figs; deduction path; minerals and nutrients within figs deduced from pattern sets, including sodium, magnesium, phosphorus, potassium, calcium, manganese, iron, nickel, copper, zinc, and strontium. Pattern sets are linked by deduction path, and the hyperlinked Internet and social media are well suited to host, share, and collaborate on common reusable pattern sets knowledge. Pattern recognition and deduction HI will be a central paradigm in AI because it does not depend on huge computing power and memory size as brute force AI does; pattern sets will be a dominant structure to represent, store, recognize knowledge, and deduce new knowledge from existing pattern sets. Humans and animals feed on figs. Connect Four demonstrations illustrate pattern sets. Magnesium benefits include muscle function, bone strength, heart function, blood pressure regulation, relaxation, sleep quality, and inflammation reduction.

Pattern Recognition and Deduction HI, Human Intelligence in AI. AI generated Voice Jessica and Subtitles. Ecosystem Patterns Set Birds Feed on Figs. Deduction Path Collection of bird families, genera and species that feed on figs. Deduced from pattern sets: Starlings feed on figs, Blackbirds feed on figs, Song thrushes feed on figs, Wood pigeons feed on figs, Jays feed on figs, House sparrows feed on figs. Green finches feed on figs. Fig birds feed on figs. Tucans feed on figs. Hornbills feed on figs. Pigeons feed on figs. Bowerbirds feed on figs. Crows feed on figs. I think the concept of pattern recognition and deduction HI, human intelligence, will be a central and main paradigm in artificial intelligence because it does not depend on huge computing power and memory size as brute force AI does as is being demonstrated with pattern sets in connect four. I also think pattern sets will be a dominant structure to represent, store, and recognize knowledge and deduce new knowledge, new pattern sets from existing knowledge, existing pattern sets. Thus pattern sets are linked to each other by deduction path and possibly other link types and as such the uncensored hyperlinked internet and social media are very well suited to host, share and collaborate in a quality on common reusable pattern sets, knowledge for people. In fact pattern recognition and deduction with pattern sets is an attempt to simulate a more human and as such smarter form of modeling and reasoning than brute force and a I trying to do it the human way. To be continued. Source2mia.org Please like, follow and share.

Pattern recognition and deduction are presented as the central paradigm for artificial intelligence, emphasizing human-like intelligence over brute-force computing. The speakers describe pattern sets as core units that store, recognize, and derive new knowledge. Pattern sets are linked to each other by a deduction path and possibly other link types, forming a structure in which new pattern sets can be generated from existing knowledge. The uncensored hyperlink Internet and social media are depicted as well-suited platforms to host, share, and collaborate on common reusable pattern-set knowledge, promoting equality in access and collaboration. Throughout the transcripts, pattern sets are given practical exemplars across domains: - Food/nutrition: figs are the source for pattern sets related to nutrients and phytochemicals, including minerals (sodium, magnesium, phosphorus, potassium, calcium, manganese, iron, nickel, copper, zinc, strontium) and various compounds (dietary fibers, vitamins, antioxidants, natural sugars, phenolic acids, flavonoids, carotenoids, organic acids). The deduction path derives health-related or nutritional conclusions from these pattern sets. - Ecosystems and dietary relationships: pattern sets describe which organisms feed on figs (humans, birds, rodents, insects, bats, primates, civets, elephants, kangaroos) and enumerate specific bird families and species that feed on figs (e.g., starlings, blackbirds, song thrushes, wood pigeons, jays, house sparrows, greenfinches, fig birds, toucans, hornbills, pigeons, bowerbirds, crows). - Magnesium and health benefits: a dedicated pattern set outlines the health benefits of a right amount of magnesium, including good muscle function, bone strength, heart function, blood pressure regulation, relaxation and stress reduction, sleep quality, blood sugar regulation, inflammation reduction, digestion support, mental well-being, and migraine reduction. The speakers reiterate that pattern recognition and deduction with pattern sets aim to simulate a more human and smarter form of modeling and reasoning than brute force AI, attempting to approximate human-like knowledge representation and inference. They stress that pattern sets will be a dominant structure for representing, storing, recognizing knowledge, and deducing new knowledge from existing pattern sets. The pattern-sets/deduction-path framework is described as enabling new knowledge to emerge from existing knowledge and as a means to facilitate collaboration and equality in access to reusable knowledge via open networks. Each speaker closes with a call to like, follow, and share, and references their sources (e.g., to mea.org, mia.org, or similar domains) as the origin of the concept and examples. The overall message emphasizes pattern recognition and deduction as a scalable, human-centered approach to AI, with diverse, domain-spanning examples illustrating how pattern sets can organize and derive actionable insights from complex data.

Pattern recognition and deduction pattern sets are proposed as a dominant structure to represent, store, and recognize knowledge and deduce new knowledge from existing pattern sets. These pattern sets are linked to each other by deduction paths and other link types. The uncensored hyperlinked Internet and social media are described as very well suited to host, share, and collaborate in equality on common reusable pattern sets knowledge for people. Pattern set deduction does not depend on huge computing power and memory size as brute force AI does, as demonstrated with pattern sets in Connect Four. The transcript presents multiple strands around phosphorus and related pattern sets. Health benefits of a right amount of phosphorus are listed as: bone strength; teeth strength; cellular energy production; DNA and RNA formation; good tissue growth; good tissue repair; good acid base balance; metabolism support; good muscle function; good nerve function; and good kidney function. Related pattern sets with the keyword health include health benefits of a right amount of magnesium and health benefits of a right amount of sodium, as well as health damages of a chronic excessive consumption of sodium and health damages of an insufficient consumption of sodium. Phosphorus pattern sets include: pattern sets are linked to each other by deduction path and other link types; the uncensored hyperlinked Internet and social media are well suited to host, share, and collaborate in equality on common reusable pattern sets knowledge for people; pattern set deduction does not depend on huge computing power and memory size as brute force AI does; to be continued. Source references include mia.org. Sources for phosphorus extraction or recycling are described as: sedimentary phosphate rocks; igneous phosphate rocks as sources for phosphorus extraction; agricultural runoffs as sources for phosphorus recycling; animal droppings as sources for phosphorus recycling; sewage streams as sources for phosphorus recycling; household wastewater streams as sources for phosphorus recycling; organic waste materials through composting as sources for phosphorus recycling; crop residues through decomposition or tillage as sources for phosphorus recycling; waste streams from industries using phosphorus (detergents, fertilizers) as sources for phosphorus recycling. Related pattern sets with the keyword phosphorus include health benefits of a right amount of phosphorus and the pattern sets with the keyword extraction are sources for salt extraction. The pattern sets emphasize equality and continued sharing, with sources2mia.org mentioned, and a call to like, follow, and share. Pattern sets for foods providing phosphorus are described as: meats provide phosphorus; seafoods provide phosphorus; eggs, yolks provide phosphorus; dairy products provide phosphorus; legumes provide phosphorus; nuts provide phosphorus; seeds provide phosphorus; whole grains provide phosphorus; vegetables provide phosphorus; processed foods provide phosphorus. Related pattern sets include provide as related to figs; minerals are provided by figs; magnesium provided by fruits; sodium provided by fresh unprocessed seafoods and fresh unprocessed vegetables. The transcript reiterates the pattern sets’ role in representing and deducing knowledge, noting that pattern sets are connected by deduction paths and other link types, and again emphasizes the suitability of the uncensored Internet for collaboration on reusable pattern sets. It ends with a “to be continued” note and references to SourceTumia.org and Source2mia.org, with requests to like, follow, and share.

Pattern recognition and deduction HI. Human intelligence in AI. AI generated voice, DORIS, and subtitles. Ecosystem pattern set minerals are provided by figs. Deduction path. Collection of minerals and trace elements within figs. Deduced from pattern sets. Sodium 11 is provided by figs. Magnesium 12 is provided by figs. Phosphorus 15 is provided by figs. Potassium 19 is provided by figs. Calcium 20 is provided by figs. Manganese 25 is provided by FIGs. Iron 26 is provided by FIGs. Nickel 28 is provided by FIGs. Copper 29 is provided by FIGs. Zinc 30 is provided by Figs. Strontium 38 is provided by Figs. Deduction source for pattern sets are provided by Figs. I think the concept of pattern recognition and deduction HI, human intelligence, will be a central and main paradigm in artificial intelligence because it does not depend on huge computing power and memory size as brute force AI does. As is being demonstrated with pattern sets in Connect Four, I also think pattern sets will be a dominant structure to represent, store, and recognize knowledge and deduce new knowledge. New pattern sets from existing knowledge. Existing pattern sets. Thus pattern sets are linked to each other by deduction path and possibly other link types and as such the uncensored hyperlink Internet and social media are very well suited to host, share and collaborate inequality on common reusable pattern sets knowledge for people. In fact, pattern recognition and deduction with pattern sets is an attempt to simulate a more human and as such smarter form of modeling and reasoning than brute force. And AI trying to do it the human way. To be continued, source tomia.org. Please like, follow and share. Speaker 1: Pattern recognition and deduction HI, human intelligence in AI. AI generated voice Christ and subtitles, ecosystem pattern set feed on figs, deduction path, collection of orders, families, and species that feed on figs, Deduced from pattern sets, humans feed on figs, birds feed on figs, rodents feed on figs, insects feed on figs, bats feed on figs, primates feed on figs, civets feed on figs, elephants feed on figs, kangaroos feed on figs. I think the concept of pattern recognition deduction HI, human intelligence, will be a central and main paradigm in artificial intelligence because it does not depend on huge computing power and memory size as brute force AI does as is being demonstrated with pattern sets in Connect Four. I also think pattern sets will be a dominant structure to represent, store, and recognize knowledge and deduce new knowledge, new pattern sets from existing knowledge, existing pattern sets. Thus pattern sets are linked to each other by deduction path and possibly other link types and as such the uncensored hyperlinked Internet and social media are very well suited to host, share and collaborate in equality on common reusable pattern sets knowledge for people. In fact pattern recognition deduction with pattern sets is an attempt to simulate a more human and as such smarter form of modeling and reasoning than brute force and AI trying to do it the human way To be continued, source to mea.org. Please like, follow, and share. Speaker 2: Pattern recognition and deduction HI, human intelligence in my AI generated voice Ethan and subtitles. Ecosystem pattern set are provided by figs deduction path, collection of nutrients and phytochemicals within figs. Deduced from pattern sets, dietary fibers are provided by figs, Vitamins are provided by figs. Minerals are provided by figs. Antioxidants are provided by figs. Natural sugars are provided by figs. Phenolic acids are provided by figs. Flavonthriols are provided by figs. Carotenoids are provided by figs. Organic acids are provided by figs. I think the concept of pattern recognition and deduction HI, human intelligence, will be a central and main paradigm in artificial intelligence because it does not depend on huge computing power and memory size as brute force I does as is being demonstrated with pattern sets in connect four. I also think pattern sets will be a dominant structure to represent, store, and recognize knowledge and deduce new knowledge, new pattern sets from existing knowledge, existing pattern sets. Thus pattern sets are linked to each other by deduction path and possibly other link types and as such the uncensored hyperlinked Internet and social media are very well suited to host, share, and collaborate inequality on common reusable pattern sets knowledge for people. In fact, pattern recognition and deduction with pattern sets is an attempt to simulate a more human and as such smarter form of modeling and reasoning than brute force, and I trying to do it the human way. To be continued, source to umia.org. Please like, follow, and share. Speaker 3: Pattern recognition and deduction HI, human intelligence in AI. AI generated voice Jessica and subtitles. Ecosystem pattern set birds feed on figs. Deduction path, collection of bird families, genera and species that feed on figs. Deduced from pattern sets, starlings feed on figs, blackbirds feed on figs, song thrushes feed on figs, wood pigeons feed on figs, jays feed on figs, house sparrows feed on figs, greenfinches feed on figs, fig birds feed on figs, Tucans feed on figs. Hornbills feed on figs. Pigeons feed on figs. Bowerbirds feed on figs. Crows feed on figs. I think the concept of pattern recognition and deduction HI, human intelligence, will be a central and main paradigm in artificial intelligence because it does not depend on huge computing power and memory size as brute force AI does as is being demonstrated with pattern sets in Connect Four. I also think pattern sets will be a dominant structure to represent, store, and recognize knowledge and deduce new knowledge, new pattern sets from existing knowledge, existing pattern sets. Thus pattern sets are linked to each other by deduction path and possibly other link types. And as such, the uncensored hyperlinked Internet and social media are very well suited to host, share and collaborate in a quality on common reusable pattern sets knowledge for people. In fact, pattern recognition and deduction with pattern sets is an attempt to simulate a more human and as such smarter form of modeling and reasoning than brute force and AI trying to do it the human way. To be continued. Source tumia.org. Please like, follow, and share.

Pattern recognition and deduction HI? Human intelligence in AI AI generated voice Lizzie and subtitles ecosystem patterns set provide magnesium deduction path. Collection of food classes that provide magnesium deduced from pattern sets. Nuts provide magnesium, seeds provide magnesium, Whole grains provide magnesium. Fruits provide magnesium. Legumes provide magnesium. Leafy green vegetables provide magnesium. Fish provides magnesium. Seafood provides magnesium. Dairy provides magnesium. I think the concept of pattern recognition and deduction HI. Human intelligence will be a central and main paradigm in artificial intelligence because it does not depend on huge computing power and memory size as brute force AI does. As is being demonstrated with pattern sets in Connect four, I also think pattern sets will be a dominant structure to represent, store and recognize knowledge and deduce new knowledge. New pattern sets from existing knowledge from existing pattern sets. Thus pattern sets are linked to each other by deduction path and possibly other link types and as such the uncensored hyperlink ad Internet and social media are very well suited to host share and collaborate in equality on common reusable pattern sets knowledge for people. In fact pattern recognition and deduction with pattern sets is an attempt to simulate a more human and as such smarter form of modeling and reasoning than brute force. An AI trying to do it the human way. To be continued. Source tomyahorg. Please like, follow and share.

Pattern Recognition and Deduction HI AI generated Voice presents a concept of Pattern Set feeding on figs, describing a deduction path that links various species to a common diet. It lists humans, birds, rodents, insects, bats, primates, civets, elephants, and kangaroos as feeding on figs, all deduced from pattern sets. The speaker asserts that pattern recognition with deduction through pattern sets will be a central main paradigm in artificial intelligence because it does not depend on huge computing power and memory size, unlike brute force AI, as demonstrated with pattern sets in Connect Four. Pattern sets are described as a dominant structure to represent, store, recognize knowledge, and deduce new knowledge and new pattern sets from existing knowledge and pattern sets. Pattern sets are connected by deduction paths and possibly other link types, making the uncensored hyperlinked internet and social media well suited to host, share, and collaborate in equality on common reusable pattern sets for people. The approach is framed as an attempt to simulate a more human and smarter form of modeling and reasoning than brute force, with an AI trying to do it the human way. The transcript concludes with a note indicating “To be continued,” referencing source2mia.org.

Pattern recognition and deduction HI, human intelligence in my I generated voice Ethan and subtitles. Ecosystem pattern set are provided by figs deduction path, collection of nutrients and phytochemicals within figs. Deduced from pattern sets, dietary fibers are provided by figs, vitamins are provided by figs, minerals are provided by figs, antioxidants are provided by figs, natural sugars are provided by figs, Phenolic acids are provided by figs. Flavonthriols are provided by figs. Carotenoids are provided by figs. Organic acids are provided by figs. I think the concept of pattern recognition and deduction, HI, human intelligence, will be a central and main paradigm in artificial intelligence because it does not depend on huge computing power and memory size as brute force I does as is being demonstrated with pattern sets in Connect four. I also think pattern sets will be a dominant structure to represent, store, and recognize knowledge and deduce new knowledge, new pattern sets from existing knowledge, existing pattern sets. Thus pattern sets are linked to each other by deduction path and possibly other link types and as such the uncensored hyperlinked Internet and social media are very well suited to host, share, and collaborate in equality on common reusable pattern sets knowledge for people. In fact, pattern recognition and deduction with pattern sets is an attempt to simulate a more human and as such smarter form of modeling and reasoning than brute force. And I trying to do it the human way. To be continued, source to umea.org. Please like, follow, and share.

Speaker 0: Pattern deduction HI, human intelligence. AI generated voice alpha. Standalone pattern set zero s one and connect four. Connect four and zero moves. Deduction path, predefined winning pattern PPPP. Number of patterns, one. Pattern list, p p p. To be continued. Sourcetome.org. Please like, follow and share. Speaker 1: Pattern deduction HI, human intelligence, AI generated voice miles, standalone pattern set1s1 and connect4, connect4 and one moves, deduction path, disk omission on pattern, number of patterns, one, pattern list, Ray0 PPP, deduced from pattern set, set zero s1 pppp, deduction path, predefined winning pattern pppp. To be continued, sourcetumia.org, please like, follow and share. Speaker 2: Human intelligence. AI generated voice Mary. Stand alone pattern set two s one and connect four. Connect four in two moves. Deduction path, empty siding fork. Number of patterns, two. Pattern list, ray zero ppp, ray zero ppp, deduced from ray zero ppp, ray zero ppp. Condition list: Because this is an empty siding, fork the rotatable empty ray position of the first pattern must be on a different column than the ray of the second pattern. In other words, their rays must be on siding columns, not be sharing a column. Deduced from pattern set s pset1 s1, ray0ppp, deduction path, disk omission on pattern. Pset1s1 Ray0ppp deduction path, disk omission on pattern. I think the concept of pattern recognition and deduction HI will be a central and main paradigm in AI because it does not depend on huge computing power and memory size as brute force AI does. In fact, pattern deduction is an attempt to simulate a more human and as such smarter form of modeling and reasoning than brute force and an AI trying to do it the human way. To be continued, source2mia.org. Please like, follow and share. Speaker 3: Pattern Recognition and Deduction HI, Human Intelligence. AI generated voice Kaili and subtitles. Stand alone pattern set two s two and connect four. Connect four and two moves. Deduction path: Empty sharing fork. Number of patterns: two. Pattern list: Re zero PPP, Re one PPP. Deduced from: Re zero PPP, Re zero PPP. Condition list: 11 empty equal: Because this is an empty sharing fork the rotatable empty position of the first pattern is by definition on the same column as the RE of the second pattern. In other words their REs must be sharing the same column, not be on different siding columns. Furthermore, for the fork to be effective one RE must be atop RE1 with depth one on top of the sub RE0 with depth zero. After all the opponent must defend on the RE0 which move transforms the RE1 PPP into RE0 PPP enabling the player to win. Deduced from pattern sets: P Set one S1, RE0 PPP I think the concept of pattern recognition and deduction HI will be a central and main paradigm in AI because it does not depend on huge computing power and memory size as brute force AI does. In fact pattern deduction is an attempt to simulate a more human and has such smarter form of modelling and reasoning than brute force, an AI tried to do it the human way. To be continued. Sourcetomia.org. Please like, follow and share. Speaker 4: Pattern Recognition and Deduction HI Human Intelligence. A generated voice patent and subtitles. All columns pattern set 2A1 in connect four. Connect four in two moves. Deduction path: All columns and opponent disc emission on depth of Re zero PPP. Number of patterns: one. Pattern list: Re one PPP. Deduced from: Re zero PPP. Condition list: At least one Re one PPP exists on the game board. In an all columns pattern set for winning in two moves every open column has a re-one PPP pattern. At least one such column with re-one PPP must exist, otherwise all columns are closed, the game is finished and a win in two moves is no longer an option of course. All open col Re1PP, in an all columns pattern set for winning in two moves every open column has a Re1PP pattern. In other words all columns are closed or have a Re-1PPP. As such an opponent's move on any open column creates a Re-0PPP enabling the player to win. Deduced from pattern sets, P Set one S one, Re zero PPP, deduction path, disk omission on pattern. I think the concept of pattern recognition and deduction HI will be a central and main paradigm in A. I because it does not depend on huge computing power and memory size as brute force A. I does. In fact pattern deduction is an attempt to simulate a more human and as such smarter form of modelling and reasoning than brute force, an AI tried to do it the human way. To be continued. Sourcetomir.org. Please like, follow and share.

Speaker 0: Pattern deduction HI, human intelligence. AI generated voice alpha. Standalone pattern set zero s one and connect four. Connect four and zero moves. Deduction path, predefined winning pattern PPPP. Number of patterns, one. Pattern list, p p p. To be continued. Sourcetome.org. Please like, follow and share. Speaker 1: Pattern deduction HI, human intelligence, AI generated voice miles, stand alone pattern set1s1 and connect4, connect4 and one moves, deduction path, disk omission on pattern, number of patterns, one, pattern list, Ray0 PPP, deduced from pattern set, set zero s1 pppp, deduction path, predefined winning pattern pppp. To be continued, sourcetumia.org, please like, follow and share. Speaker 2: Human intelligence. AI generated voice Mary. Stand alone pattern set two s one and connect four. Connect four in two moves. Deduction path, empty siding fork. Number of patterns, two. Pattern list, ray zero ppp, ray zero ppp, deduced from ray zero ppp, ray zero ppp. Condition list: Because this is an empty siding, fork the rotatable empty ray position of the first pattern must be on a different column than the ray of the second pattern. In other words, their rays must be on siding columns, not be sharing a column. Deduced from pattern set s pset1 s1, ray0ppp, deduction path, disk omission on pattern. Pset1s1 Ray0ppp deduction path, disk omission on pattern. I think the concept of pattern recognition and deduction HI will be a central and main paradigm in AI because it does not depend on huge computing power and memory size as brute force AI does. In fact, pattern deduction is an attempt to simulate a more human and as such smarter form of modeling and reasoning than brute force and AI trying to do it the human way. To be continued, source2mia.org. Please like, follow and share. Speaker 3: Pattern Recognition and Deduction HI, Human Intelligence. AI generated voice Kaili and subtitles. Stand alone pattern set two s two and connect four. Connect four and two moves. Deduction path: Empty sharing fork. Number of patterns: two. Pattern list: Re zero PPP, Re one PPP. Deduced from: Re zero PPP, Re zero PPP. Condition list: 11 empty equal: Because this is an empty sharing fork the rotatable empty position of the first pattern is by definition on the same column as the RE of the second pattern. In other words their REs must be sharing the same column, not be on different siding columns. Furthermore, for the fork to be effective one RE must be atop RE1 with depth one on top of the sub RE0 with depth zero. After all the opponent must defend on the RE0 which move transforms the RE1 PPP into RE0 PPP enabling the player to win. Deduced from pattern sets: P Set one S1, RE0 PPP I think the concept of pattern recognition and deduction HI will be a central and main paradigm in AI because it does not depend on huge computing power and memory size as brute force AI does. In fact pattern deduction is an attempt to simulate a more human and has such smarter form of modelling and reasoning than brute force, an AI trying to do it the human way. To be continued. Sourcetumia.org. Please like, follow and share. Speaker 4: Pattern Recognition and Deduction HI Human Intelligence. A generated voice patent and subtitles. All columns pattern set 2A1 in connect four. Connect four in two moves. Deduction path: All columns and opponent disc emission on depth of Re zero PPP. Number of patterns: one. Pattern list: Re one PPP. Deduced from: Re zero PPP. Condition list: At least one Re one PPP, at least one Re one PPP exists on the game board. In an all columns pattern set for winning in two moves every open column has a re-one PPP pattern. At least one such column with re-one PPP must exist, otherwise all columns are closed, the game is finished and a win in two moves is no longer an option of course. All open col Re1PP, in an all columns pattern set for winning in two moves every open column has a Re1PP pattern. In other words all columns are closed or have a Re-1PPP. As such an opponent's move on any open column creates a Re-0PPP enabling the player to win. Deduced from pattern sets, P Set one S one, Re zero PPP, deduction path, disk omission on pattern. I think the concept of pattern recognition and deduction HI will be a central and main paradigm in AI because it does not depend on huge computing power and memory size as brute force AI does. In fact pattern deduction is an attempt to simulate a more human and as such smarter form of modelling and reasoning than brute force, an AI tried to do it the human way. To be continued. Sourcetomir.org. Please like, follow and share.