Furtherium

furtherium

AI technology is firmly carving out a niche in defense technology. News reports refer to partnership agreements between large defense technology corporations such as Northrop Grumman, Lockheed Martin, Raytheon, and startups in Artificial Intelligence/Machine Learning (AI/ML), Image Intelligence (IMINT) Recognition, Battlefield Awareness, Multi‐Domain Battle Management Team (MBMT) Mobility Platform, Tactical Augmented Reality (TAR), Radio Frequency and Wireless Surveillance (RFWS) Systems. At the same time, defense startups like Palantir and Anduril, which have relied on the use of AI since their inception, have now emerged as major game-changing market players. Undoubtedly, this trend will continue in the future and we will soon see significant changes in the direction of enhanced national security and deployed defense technologies. As proof, Project Maven, announced in 2017 according to various sources, is being tested in combat use in military conflicts in Ukraine and Israel. A wearable mobile platform with a high-performance computing module within the Soldier-as-Sensor concept is expected to complement the Battlefield Management System (BMS) and Joint All-Domain Command and Control (JADC2) ecosystems. At least a few defense agencies periodically publish innovation requests for these and related research and technology areas in the prototype stage. Today's highly mobile battlefield threats and higher demands on the cognitive capabilities of operators are driving the need to act simultaneously on multiple fronts. Everyone is required to have accurate Tactical Situational Awareness, Friend-or-Foe Identification, Synthetic Day/Night Vision, BLOS Communications, Sensors, Signal Intelligence, RF Wideband Digital Beamforming, and be an element for sharing this information in peer-to-peer networks. Until recently, some technological limitations have prevented the creation of a convenient mobile platform with dimensions that would allow a person to wear an electronic device for extended periods. For several years, Microsoft tried to adapt its HoloLense 2 device for the IVAS defense project. However, immersive technologies (AR/MR) designed for entertainment, education and training are not well-suited for the military. At Furtherium, my team and I initially created the concept of AI-powered Tactical Situational Awareness Mobility Platform primarily for the military, security forces, rescuers, and firefighters. The key advantages of this technology are its compact design, fast performance, integration of all important functions, and affordable price. And a special feature is the application of several AI technologies on a local device. I founded Furtherium in 2021 and started developing an integrated product ARHUDFM (Augmented Reality Head-Up Display Fullface Mask) - Hardware modules, SaaS and Healthcare modules. Several detection and recognition functions cover visual information in the visible and infrared spectrum, sound and radio frequency waves over a very wide range, passive radar signatures and an EOD scanner for explosive detection. The core of the technology is not only pre-trained Machine Learning models, but also neural network generative AI models that are trained together with each user. For this purpose, advanced CPU and NPU technologies are used in each device. You could say this is the next step in using generative AI in mobile platforms, focused not only on defense applications, with huge dual-use potential. Fine-tuning a local model on a user's device still looks unfamiliar right now, but that's the future. In addition to the key goals of detection and recognition, other basic functions are Omnichannel Messenger, Media Capture and Exchange, Ballistic Fire Assistant and Spotter, Multi-Domain Operations, RC Universal Controller for drones and robots. You don't have to look into the future to understand the trends, just open YouTube and see for yourself the training programs at the U.S. Marine Corps and Army. I'd like to share the new YouTube video we created that demonstrates the capabilities of my startup's mobile platform, controlled primarily by a voice assistant that adapts to each user. https://www.youtube.com/watch?v=kIUt2jbYHMs&embedable=true It seems natural and logical now, but we didn't come to this immediately, it took several years of research into behavioral capabilities, cognitive constraints, tactical documentation and the capabilities of different electronic component architectures. The technical requirements of the military are very different from civilian applications. This applies not only to Hardware, but also to Software, including how generative AI models should be used, what criteria they are required to meet. Many features must be considered when designing for military applications: Night Vision and Augmented Reality without outward illumination, protection against ionizing radiation, main and backup power system, battery life, active cooling, shock wave and fragments exposure, encryption and hopping frequencies for data exchange, reduced traffic while maintaining data quality. It would be wrong to think about the protection of the device and not provide for the protection of the user. For this purpose, several options are created simultaneously for hearing protection and protection against concussion, eye and face protection, respiratory protection, built-in drinking system, automatic tourniquets to stop acute bleeding. Sensors in the user's arms, legs, back, and chest allow health monitoring during exercises, training, and tactical missions. SAM (Serviceable Addressable Market) for this technology estimates exceed $31B and include markets in over 32 NATO countries and its allies. Amid the Research, Development, Test & Evaluation budget of the U.S. DoD alone of $148B this looks promising. Military innovation budgets are on the rise, that's another trend today. My startup's project involves integrating products from companies such as Palantir, Anduril, Teledyne FLIR, Shield AI, Epirus, Elbit Systems, Raytheon, Northrop Grumman, and Thales Group. Combining non-competing systems creates unique synergies. I am also pleased to announce that we are close to raising funds. Investors are expected to include companies with expertise in the Defense and Security area. More Details Furtherium, Inc. | Website | Wiki | Community | Pitch Deck AI technology is firmly carving out a niche in defense technology. News reports refer to partnership agreements between large defense technology corporations such as Northrop Grumman, Lockheed Martin, Raytheon, and startups in Artificial Intelligence/Machine Learning (AI/ML), Image Intelligence (IMINT) Recognition, Battlefield Awareness, Multi‐Domain Battle Management Team (MBMT) Mobility Platform, Tactical Augmented Reality (TAR), Radio Frequency and Wireless Surveillance (RFWS) Systems. At the same time, defense startups like Palantir and Anduril, which have relied on the use of AI since their inception, have now emerged as major game-changing market players. Undoubtedly, this trend will continue in the future and we will soon see significant changes in the direction of enhanced national security and deployed defense technologies. As proof, Project Maven, announced in 2017 according to various sources, is being tested in combat use in military conflicts in Ukraine and Israel. A wearable mobile platform with a high-performance computing module within the Soldier-as-Sensor concept is expected to complement the Battlefield Management System (BMS) and Joint All-Domain Command and Control (JADC2) ecosystems. At least a few defense agencies periodically publish innovation requests for these and related research and technology areas in the prototype stage. Today's highly mobile battlefield threats and higher demands on the cognitive capabilities of operators are driving the need to act simultaneously on multiple fronts. Everyone is required to have accurate Tactical Situational Awareness, Friend-or-Foe Identification, Synthetic Day/Night Vision, BLOS Communications, Sensors, Signal Intelligence, RF Wideband Digital Beamforming, and be an element for sharing this information in peer-to-peer networks. Until recently, some technological limitations have prevented the creation of a convenient mobile platform with dimensions that would allow a person to wear an electronic device for extended periods. For several years, Microsoft tried to adapt its HoloLense 2 device for the IVAS defense project. However, immersive technologies (AR/MR) designed for entertainment, education and training are not well-suited for the military. At Furtherium, my team and I initially created the concept of AI-powered Tactical Situational Awareness Mobility Platform primarily for the military, security forces, rescuers, and firefighters. The key advantages of this technology are its compact design, fast performance, integration of all important functions, and affordable price. And a special feature is the application of several AI technologies on a local device. I founded Furtherium in 2021 and started developing an integrated product ARHUDFM (Augmented Reality Head-Up Display Fullface Mask) - Hardware modules, SaaS and Healthcare modules. Several detection and recognition functions cover visual information in the visible and infrared spectrum, sound and radio frequency waves over a very wide range, passive radar signatures and an EOD scanner for explosive detection. The core of the technology is not only pre-trained Machine Learning models, but also neural network generative AI models that are trained together with each user. For this purpose, advanced CPU and NPU technologies are used in each device. You could say this is the next step in using generative AI in mobile platforms, focused not only on defense applications, with huge dual-use potential. Fine-tuning a local model on a user's device still looks unfamiliar right now, but that's the future. In addition to the key goals of detection and recognition, other basic functions are Omnichannel Messenger, Media Capture and Exchange, Ballistic Fire Assistant and Spotter, Multi-Domain Operations, RC Universal Controller for drones and robots. You don't have to look into the future to understand the trends, just open YouTube and see for yourself the training programs at the U.S. Marine Corps and Army. I'd like to share the new YouTube video we created that demonstrates the capabilities of my startup's mobile platform, controlled primarily by a voice assistant that adapts to each user. the new YouTube video https://www.youtube.com/watch?v=kIUt2jbYHMs&embedable=true https://www.youtube.com/watch?v=kIUt2jbYHMs&embedable=true It seems natural and logical now, but we didn't come to this immediately, it took several years of research into behavioral capabilities, cognitive constraints, tactical documentation and the capabilities of different electronic component architectures. The technical requirements of the military are very different from civilian applications. This applies not only to Hardware, but also to Software, including how generative AI models should be used, what criteria they are required to meet. Many features must be considered when designing for military applications: Night Vision and Augmented Reality without outward illumination, protection against ionizing radiation, main and backup power system, battery life, active cooling, shock wave and fragments exposure, encryption and hopping frequencies for data exchange, reduced traffic while maintaining data quality. It would be wrong to think about the protection of the device and not provide for the protection of the user. For this purpose, several options are created simultaneously for hearing protection and protection against concussion, eye and face protection, respiratory protection, built-in drinking system, automatic tourniquets to stop acute bleeding. Sensors in the user's arms, legs, back, and chest allow health monitoring during exercises, training, and tactical missions. SAM (Serviceable Addressable Market) for this technology estimates exceed $31B and include markets in over 32 NATO countries and its allies. Amid the Research, Development, Test & Evaluation budget of the U.S. DoD alone of $148B this looks promising. Military innovation budgets are on the rise, that's another trend today. My startup's project involves integrating products from companies such as Palantir, Anduril, Teledyne FLIR, Shield AI, Epirus, Elbit Systems, Raytheon, Northrop Grumman, and Thales Group. Combining non-competing systems creates unique synergies. I am also pleased to announce that we are close to raising funds. Investors are expected to include companies with expertise in the Defense and Security area. More Details Furtherium, Inc. | Website | Wiki | Community | Pitch Deck Website Wiki Community Pitch Deck

AI's Influence is Going to Go Deeper Than Just the Corporate Sector

AI এর প্রভাব শুধু কর্পোরেট সেক্টরের চেয়ে গভীরে যেতে চলেছে৷

Der Einfluss der KI wird über den Unternehmenssektor hinausgehen

La influencia de la IA va a llegar más allá del sector corporativo

L’influence de l’IA va s’étendre au-delà du secteur privé

एआई का प्रभाव सिर्फ कॉर्पोरेट क्षेत्र तक ही सीमित नहीं रहेगा

AIの影響は企業部門だけにとどまらない

AI의 영향력은 기업 부문에만 국한되지 않고 더욱 깊어질 것입니다.

A influência da IA vai além do setor corporativo

Влияние ИИ выйдет за рамки корпоративного сектора

Yapay Zekanın Etkisi Sadece Kurumsal Sektörle Sınırlı Kalmayacak

Ảnh hưởng của AI sẽ không chỉ giới hạn trong lĩnh vực doanh nghiệp

人工智能的影响将不仅仅局限于企业领域

Additional Numerical Experiments on K-SIF and SIF: Depth, Noise, and Discrimination Power

تجارب عددية إضافية على K-SIF وSIF: العمق والضوضاء وقوة التمييز

Πρόσθετα αριθμητικά πειράματα σε K-SIF και SIF: Βάθος, θόρυβος και ισχύς διάκρισης

Experimentos numéricos adicionales sobre K-SIF y SIF: profundidad, ruido y poder de discriminación

Muita numeerisia kokeita K-SIF:llä ja SIF:llä: syvyys, kohina ja erotteluteho

További numerikus kísérletek a K-SIF-en és SIF-en: mélység, zaj és megkülönböztető teljesítmény

Ulteriori esperimenti numerici su K-SIF e SIF: profondità, rumore e potere di discriminazione

K-SIF と SIF に関する追加の数値実験: 深度、ノイズ、識別力

დამატებითი რიცხვითი ექსპერიმენტები K-SIF-ზე და SIF-ზე: სიღრმე, ხმაური და დისკრიმინაციის ძალა

Dodatkowe eksperymenty numeryczne dotyczące K-SIF i SIF: głębokość, szum i moc dyskryminacyjna

Experimentos numéricos adicionais em K-SIF e SIF: profundidade, ruído e poder de discriminação

Додаткові чисельні експерименти з K-SIF і SIF: глибина, шум і потужність дискримінації

Iimvavanyo ezongezelelweyo zamanani kwi-K-SIF kunye ne-SIF: Ubunzulu, ingxolo, kunye namandla ocalucalulo

Recently, my friend with a strong desire to make a difference in the world and deeply interested in the political future of society—asked me a question that sounded both paradoxical and provocative: “How can corruption be put to work for the state?” At first glance, the idea of using corruption as a tool for the state’s benefit seems controversial, but it raises an important question about the nature of governance and approaches to achieving public good in modern societies. These reflections, however, led me to another, more interesting idea: that the best path to building a prosperous society for everyone is through integrating economic growth and environmental protection as equal goals, handing these tasks over to technologies that will emerge very soon. I am convinced that only artificial general intelligence (AGI) can reliably and effectively manage the achievement of these two essential objectives in the future. But let’s start with corruption, one of the most deeply rooted problems in various countries. Corruption can be found in both democratic and authoritarian systems, in nations with high and low levels of development. It functions as a parallel power structure, where personal interests replace public ones and distort democratic principles. In research Corruption and Government: Causes, Consequences, and Reform, Susan Rose-Ackerman and Bonnie J. Palifka emphasize that corruption infiltrates even those structures meant to uphold justice and transparency, undermining public trust in institutions—a phenomenon we can observe in many countries, such as Russia, China, and North Korea. Transparency International, which publishes the Corruption Perceptions Index annually, confirms that fighting corruption remains a pressing issue on a global scale. Despite the efforts of anti-corruption organizations and reformers, corruption often remains a persistent and seemingly unavoidable part of political systems. It is worth noting that history has seen attempts at “managed” corruption, where instead of eradicating it completely, authorities aimed to minimize its harmful effects. For example, in some authoritarian regimes, corruption is tolerated as a way to maintain elite loyalty and system stability. Michael Johnston, in his book Syndromes of Corruption: Wealth, Power, and Democracy, explores the phenomenon of corruption and argues that such “managed” corruption may temporarily help sustain stability but ultimately deepens social inequality and increases public dissatisfaction in the long run. In short, corruption cannot be turned into something beneficial, as the idea of "useful" corruption encounters several fundamental issues: Ethical contradictions. Legalizing corruption or using it for state purposes undermines principles of justice and equality. Such a system becomes vulnerable and loses legitimacy.


Economic inefficiency. Corruption leads to resource waste and reduces the effectiveness of government management.


Social inequality. Corruption deepens social divides, as resources meant to improve life for all citizens are redirected to benefit a narrow group of individuals. An interesting aspect of our discussion is that the ideal economic model for humanity should combine sustainable economic development with environmental protection. The United Nations, through its Sustainable Development Goals (SDGs), emphasizes that only balanced and sustainable economic growth can improve quality of life on the planet while minimizing environmental impact. Thus, a crucial aspect here is the integration of economic growth with environmental goals, which modern scientists and researchers already consider the only path to long-term well-being. Economist Jeffrey D. Sachs, in his book The Age of Sustainable Development, argues that a society’s happiness can be measured not only by GDP growth but also by its level of environmental sustainability, air and water quality, access to green spaces, and social equality. The combination of these factors helps create a society in which each individual feels part of a shared prosperity, while the environment remains viable for future generations. But what does AGI, technocracy, and the coming technological revolution have to do with this? In light of the above conclusions about corruption and the challenges of sustainable development, it’s clear that traditional management models, based on human decisions, are often unable to effectively address issues of sustainable growth. Sadly, people alone cannot fully help people. Modern technologies, especially artificial intelligence, have the potential to offer more flexible and precise solutions. I argue that AGI will be capable of managing the economy by striking a balance between economic growth and environmental sustainability. In book Life 3.0: Being Human in the Age of Artificial Intelligence, Max Tegmark notes that AGI will be able to process massive amounts of statistical data, which is essentially what the economy is built on—data analysis and interpretation. Works like The Second Machine Age by Erik Brynjolfsson and Andrew McAfee emphasize that AI has the potential to transform the management of social and economic processes, helping to reduce the impact of human weaknesses and biases. To me, this means that AGI could effectively allocate resources in the future to serve the public good, taking into account both current and long-term needs of society and our planet’s environment. I believe that the development of AGI will pave the way for a technocratic model of governance, where the economy becomes not just a tool for growth, but a system focused on creating conditions for societal happiness and well-being. In conclusion, I believe that humanity's best path forward lies not in attempts to adapt corruption for state needs, but in the pursuit of sustainable development grounded in advanced technologies. Corruption, even when "under control," undermines trust in institutions, slows progress, and deepens inequality. Instead of seeking "useful" corruption, humanity should focus on technologies that can provide long-term economic growth while also promoting environmental protection—key aspects upon which the well-being of future generations depends. The development of artificial general intelligence (AGI) could be the starting point for this progress. AGI has the potential to bring a new level of efficiency and transparency to governance, where traditional problems like corruption would cease to exist, as all processes would be focused on the public good. Furthermore, AGI could become a tool for balancing economic development with the preservation of natural resources. In a world where sustainable management is essential for the very possibility of life on the planet, such a model could be a solution and lifeline for future generations. In the face of global challenges such as climate change and the depletion of natural resources, it is clear that only the alignment of economic and environmental goals will create a harmonious future. Sustainable development, managed by AGI, has the potential to ensure long-term stability in which both public welfare and the environment are preserved for the benefit of future generations. Thus, AGI could offer humanity a completely new paradigm of governance, where corruption becomes obsolete, and steady economic growth along with environmental stewardship form the solid foundation for the happiness and prosperity of society as a whole. Recently, my friend with a strong desire to make a difference in the world and deeply interested in the political future of society—asked me a question that sounded both paradoxical and provocative: “How can corruption be put to work for the state?” At first glance, the idea of using corruption as a tool for the state’s benefit seems controversial, but it raises an important question about the nature of governance and approaches to achieving public good in modern societies. These reflections, however, led me to another, more interesting idea: that the best path to building a prosperous society for everyone is through integrating economic growth and environmental protection as equal goals , handing these tasks over to technologies that will emerge very soon. I am convinced that only artificial general intelligence (AGI) can reliably and effectively manage the achievement of these two essential objectives in the future. as equal goals But let’s start with corruption, one of the most deeply rooted problems in various countries. Corruption can be found in both democratic and authoritarian systems, in nations with high and low levels of development. It functions as a parallel power structure, where personal interests replace public ones and distort democratic principles. In research Corruption and Government: Causes, Consequences, and Reform, Susan Rose-Ackerman and Bonnie J. Palifka emphasize that corruption infiltrates even those structures meant to uphold justice and transparency, undermining public trust in institutions—a phenomenon we can observe in many countries, such as Russia, China, and North Korea. Corruption and Government: Causes, Consequences, and Reform , Corruption and Government: Causes, Consequences, and Reform Corruption and Government: Causes, Consequences, and Reform Transparency International, which publishes the Corruption Perceptions Index annually , confirms that fighting corruption remains a pressing issue on a global scale. Despite the efforts of anti-corruption organizations and reformers, corruption often remains a persistent and seemingly unavoidable part of political systems. Corruption Perceptions Index Corruption Perceptions Index Corruption Perceptions Index annually annually It is worth noting that history has seen attempts at “managed” corruption, where instead of eradicating it completely, authorities aimed to minimize its harmful effects. For example, in some authoritarian regimes, corruption is tolerated as a way to maintain elite loyalty and system stability. Michael Johnston, in his book Syndromes of Corruption: Wealth, Power, and Democracy, explores the phenomenon of corruption and argues that such “managed” corruption may temporarily help sustain stability but ultimately deepens social inequality and increases public dissatisfaction in the long run. Syndromes of Corruption: Wealth, Power, and Democracy , Syndromes of Corruption: Wealth, Power, and Democracy Syndromes of Corruption: Wealth, Power, and Democracy In short, corruption cannot be turned into something beneficial, as the idea of "useful" corruption encounters several fundamental issues: Ethical contradictions. Legalizing corruption or using it for state purposes undermines principles of justice and equality. Such a system becomes vulnerable and loses legitimacy. Economic inefficiency. Corruption leads to resource waste and reduces the effectiveness of government management. Social inequality. Corruption deepens social divides, as resources meant to improve life for all citizens are redirected to benefit a narrow group of individuals. Ethical contradictions. Legalizing corruption or using it for state purposes undermines principles of justice and equality. Such a system becomes vulnerable and loses legitimacy. Ethical contradictions. Legalizing corruption or using it for state purposes undermines principles of justice and equality. Such a system becomes vulnerable and loses legitimacy. Ethical contradictions. Economic inefficiency. Corruption leads to resource waste and reduces the effectiveness of government management. Economic inefficiency. Corruption leads to resource waste and reduces the effectiveness of government management. Economic inefficiency. Social inequality. Corruption deepens social divides, as resources meant to improve life for all citizens are redirected to benefit a narrow group of individuals. Social inequality . Corruption deepens social divides, as resources meant to improve life for all citizens are redirected to benefit a narrow group of individuals. Social inequality An interesting aspect of our discussion is that the ideal economic model for humanity should combine sustainable economic development with environmental protection. The United Nations, through its Sustainable Development Goals ( SDGs ), emphasizes that only balanced and sustainable economic growth can improve quality of life on the planet while minimizing environmental impact. SDGs SDGs SDGs Thus, a crucial aspect here is the integration of economic growth with environmental goals, which modern scientists and researchers already consider the only path to long-term well-being. Economist Jeffrey D. Sachs, in his book The Age of Sustainable Development, argues that a society’s happiness can be measured not only by GDP growth but also by its level of environmental sustainability, air and water quality, access to green spaces, and social equality. The combination of these factors helps create a society in which each individual feels part of a shared prosperity, while the environment remains viable for future generations. The Age of Sustainable Development , The Age of Sustainable Development The Age of Sustainable Development But what does AGI, technocracy, and the coming technological revolution have to do with this? In light of the above conclusions about corruption and the challenges of sustainable development, it’s clear that traditional management models, based on human decisions, are often unable to effectively address issues of sustainable growth. Sadly, people alone cannot fully help people. Modern technologies, especially artificial intelligence, have the potential to offer more flexible and precise solutions. I argue that AGI will be capable of managing the economy by striking a balance between economic growth and environmental sustainability. In book Life 3.0: Being Human in the Age of Artificial Intelligence, Max Tegmark notes that AGI will be able to process massive amounts of statistical data, which is essentially what the economy is built on—data analysis and interpretation. Works like The Second Machine Age by Erik Brynjolfsson and Andrew McAfee emphasize that AI has the potential to transform the management of social and economic processes, helping to reduce the impact of human weaknesses and biases. Life 3.0: Being Human in the Age of Artificial Intelligence , Life 3.0: Being Human in the Age of Artificial Intelligence Life 3.0: Being Human in the Age of Artificial Intelligence The Second Machine Age The Second Machine Age The Second Machine Age To me, this means that AGI could effectively allocate resources in the future to serve the public good, taking into account both current and long-term needs of society and our planet’s environment. I believe that the development of AGI will pave the way for a technocratic model of governance, where the economy becomes not just a tool for growth, but a system focused on creating conditions for societal happiness and well-being. In conclusion, I believe that humanity's best path forward lies not in attempts to adapt corruption for state needs, but in the pursuit of sustainable development grounded in advanced technologies. Corruption, even when "under control," undermines trust in institutions, slows progress, and deepens inequality. Instead of seeking "useful" corruption, humanity should focus on technologies that can provide long-term economic growth while also promoting environmental protection—key aspects upon which the well-being of future generations depends. The development of artificial general intelligence (AGI) could be the starting point for this progress. AGI has the potential to bring a new level of efficiency and transparency to governance, where traditional problems like corruption would cease to exist, as all processes would be focused on the public good. Furthermore, AGI could become a tool for balancing economic development with the preservation of natural resources. In a world where sustainable management is essential for the very possibility of life on the planet, such a model could be a solution and lifeline for future generations. In the face of global challenges such as climate change and the depletion of natural resources, it is clear that only the alignment of economic and environmental goals will create a harmonious future. Sustainable development, managed by AGI, has the potential to ensure long-term stability in which both public welfare and the environment are preserved for the benefit of future generations. Thus, AGI could offer humanity a completely new paradigm of governance, where corruption becomes obsolete, and steady economic growth along with environmental stewardship form the solid foundation for the happiness and prosperity of society as a whole.

Could Artificial General Intelligence Make Government Corruption Obsolete? 

Može li vještačka opća inteligencija učiniti korupciju vlade zastarjelom? 

¿Podría la Inteligencia Artificial General hacer obsoleta la corrupción gubernamental?

Inteligentzia Orokor Artifizialak Gobernuaren ustelkeria zaharkitu al dezake? 

Podería a intelixencia xeral artificial facer obsoleta a corrupción do goberno? 

क्या कृत्रिम सामान्य बुद्धिमत्ता सरकारी भ्रष्टाचार को ख़त्म कर सकती है?

A mesterséges általános intelligencia elavulttá teheti a kormányzati korrupciót? 

האם בינה כללית מלאכותית יכולה להפוך את השחיתות השלטונית למיושנת? 

汎用人工知能は政府の腐敗をなくすことができるか？

ປັນຍາທຽມທົ່ວໄປສາມາດເຮັດໃຫ້ການສໍ້ລາດບັງຫຼວງຂອງລັດຖະບານລ້າສະໄຫມໄດ້ບໍ? 

Может ли искусственный интеллект сделать коррупцию в правительстве ненужной?

Sirdoonka Guud ee macmalka ahi ma ka dhigi karaa musuqmaasuqa dawladda mid duugoobay? 

Kan artificiell allmän intelligens göra statlig korruption föråldrad? 

As a participant in this year's Hacktoberfest, I created an AI chatbot called Technical Writer. This AI chatbot, built with Coze, is designed for beginners and technical writing experts. It is also integrated into the Technical Writing Mentorship Program (TWMP) learning site as a contribution to the TWMP community, founded by Nwokocha Wisdom. With his team, they have successfully trained over thirty technical writers, including me, in various technical fields. Technical Writer helps technical writers by: Providing the right answers and career paths in technical writing.
Suggesting projects for technical writers to build their portfolios.
Simplifying technical writing terminologies with real-life examples. Why Technical Writers Matter in Technical Writing As a technical advocate who frequently shares the importance of technical writing on social media, I often receive direct messages from people asking questions like: How can I start in technical writing?
What courses should I take to become a technical writer? And many more questions. Sometimes, I find these questions overwhelming, even though I enjoy answering them. I built this chatbot on available courses on TWMP’s site and an API documentation course by Tom Johnson to help answer and guide technical writers in their journey. Demo https://youtu.be/aVrPfzu0W-s?embedable=true Coze Agent Store: TechnicalWriter Discord Chatbot: TechnicalWriter How I Built Technical Writer These are the steps I took in building this chatbot: Adding the Character and skills I described my chatbot character and skill in the Persona & Prompt field and then optimized the character and skill. Knowledge Resources As mentioned earlier, the chatbot response will be based on the courses available on TWMP and API documentation course. To do this, I added these courses using the Knowledge feature. I batch-added the TWMP and API doc Course base URLs which took about 20 mins to process. I added these resources using “Add to agent.” The reasons why I used only these resources are: The courses were written by experts in technical writing with proven records.


These courses have helped me and many others become top technical writers and excellent contributors for reputable organizations like Google and JSON Schema. Chat Experience Welcoming Note I added a friendly welcoming note to the chatbot which gives an overview of what the chatbot is all about using the “opening text” feature. Auto-suggestion To enhance further engagement and clarity for the users, I added the auto-suggestion feature with a custom prompt to keep the chatbot from within the scope of the chatbot. Voice Chat I also added a voice chat feature to the chatbot to ensure that people with visual impairments are not excluded. This promotes accessibility for users worldwide. Furthermore, I enable communication in all available languages such as Arabic, Japanese, French, etc. Discord Integration Since TWMP’s community is on Discord, I integrated this chatbot into a Discord bot so that community members can interact with it directly. I created a New application and named it after the chatbot. Then I copied the Bot token and added it to the chatbot. This link was sent to the group admin and was added to the server. Submitting the Chatbot to the Agent Store To ensure this chatbot is not used solely by the local community, I submitted it to the Coze agent store to help technical writers worldwide attain their skills and expertise in technical writing. It was submitted under the 'Writing’ category. So if you head over to the Writing category, and search for “TechnicalWriter”, you will see it there Don’t forget to drop a comment, like, and share with others Adding the Chatbot to the Learning Site I copied the chatbot Web SDK.



I added it to the repo. Result: The chatbot icon is displayed on the site. As it responds to the user, it also adds a reference, as shown above. Final Note This process took me one week to complete because I built this chatbot for an open-source community, so it had to go through the proper procedures. I was asked to change the icon to match the community logo. Some of the challenges I faced were: Trying to modify the height of the chatbot.
I couldn't add an avatar or image on behalf of the user. Despite these challenges, I believe more features will be added. Thanks to the documentation and my experience creating a Telegram bot, I also learned how to create a Discord chatbot for the first time. If you find this chatbot helpful, don’t hesitate to add it to your community. As a participant in this year's Hacktoberfest, I created an AI chatbot called Technical Writer . This AI chatbot, built with Coze , is designed for beginners and technical writing experts. It is also integrated into the Technical Writing Mentorship Program (TWMP) learning site as a contribution to the TWMP community, founded by Nwokocha Wisdom . With his team, they have successfully trained over thirty technical writers, including me, in various technical fields. Technical Writer Coze Technical Writing Mentorship Program (TWMP) Technical Writing Mentorship Program (TWMP) Nwokocha Wisdom Technical Writer helps technical writers by: Technical Writer Providing the right answers and career paths in technical writing. Suggesting projects for technical writers to build their portfolios. Simplifying technical writing terminologies with real-life examples. Providing the right answers and career paths in technical writing. Suggesting projects for technical writers to build their portfolios. Simplifying technical writing terminologies with real-life examples. Why Technical Writers Matter in Technical Writing As a technical advocate who frequently shares the importance of technical writing on social media, I often receive direct messages from people asking questions like: How can I start in technical writing? What courses should I take to become a technical writer? How can I start in technical writing? What courses should I take to become a technical writer? And many more questions. Sometimes, I find these questions overwhelming, even though I enjoy answering them. I built this chatbot on available courses on TWMP’s site and an API documentation course by Tom Johnson to help answer and guide technical writers in their journey. API documentation course Tom Johnson Demo https://youtu.be/aVrPfzu0W-s?embedable=true https://youtu.be/aVrPfzu0W-s?embedable=true Coze Agent Store: TechnicalWriter TechnicalWriter Discord Chatbot: TechnicalWriter TechnicalWriter How I Built Technical Writer These are the steps I took in building this chatbot: Adding the Character and skills I described my chatbot character and skill in the Persona & Prompt field and then optimized the character and skill. Persona & Prompt Knowledge Resources As mentioned earlier, the chatbot response will be based on the courses available on TWMP and API documentation course. To do this, I added these courses using the Knowledge feature. Knowledge I batch-added the TWMP and API doc Course base URLs which took about 20 mins to process. I batch-added the TWMP and API doc Course base URLs which took about 20 mins to process. I added these resources using “Add to agent.” I added these resources using “Add to agent.” I added these resources using “ Add to agent.” Add to agent.” The reasons why I used only these resources are: The courses were written by experts in technical writing with proven records. These courses have helped me and many others become top technical writers and excellent contributors for reputable organizations like Google and JSON Schema. The courses were written by experts in technical writing with proven records. The courses were written by experts in technical writing with proven records. These courses have helped me and many others become top technical writers and excellent contributors for reputable organizations like Google and JSON Schema. These courses have helped me and many others become top technical writers and excellent contributors for reputable organizations like Google and JSON Schema. Chat Experience Welcoming Note I added a friendly welcoming note to the chatbot which gives an overview of what the chatbot is all about using the “ opening text” feature. opening text” Auto-suggestion To enhance further engagement and clarity for the users, I added the auto-suggestion feature with a custom prompt to keep the chatbot from within the scope of the chatbot. Voice Chat I also added a voice chat feature to the chatbot to ensure that people with visual impairments are not excluded. This promotes accessibility for users worldwide. Furthermore, I enable communication in all available languages such as Arabic, Japanese, French, etc. Discord Integration Since TWMP’s community is on Discord, I integrated this chatbot into a Discord bot so that community members can interact with it directly. I created a New application and named it after the chatbot. I created a New application and named it after the chatbot. Then I copied the Bot token and added it to the chatbot. Then I copied the Bot token and added it to the chatbot. Then I copied the Bot token and added it to the chatbot. This link was sent to the group admin and was added to the server. Submitting the Chatbot to the Agent Store To ensure this chatbot is not used solely by the local community, I submitted it to the Coze agent store to help technical writers worldwide attain their skills and expertise in technical writing. It was submitted under the ' Writing’ category. Writing’ So if you head over to the Writing category, and search for “TechnicalWriter”, you will see it there “ TechnicalWriter ”, TechnicalWriter Don’t forget to drop a comment, like, and share with others Don’t forget to drop a comment, like, and share with others Adding the Chatbot to the Learning Site I copied the chatbot Web SDK. I added it to the repo. I copied the chatbot Web SDK. I copied the chatbot Web SDK. I added it to the repo. I added it to the repo. Result: The chatbot icon is displayed on the site. As it responds to the user, it also adds a reference, as shown above. Final Note This process took me one week to complete because I built this chatbot for an open-source community, so it had to go through the proper procedures. I was asked to change the icon to match the community logo. Some of the challenges I faced were: Trying to modify the height of the chatbot. I couldn't add an avatar or image on behalf of the user. Trying to modify the height of the chatbot. I couldn't add an avatar or image on behalf of the user. Despite these challenges, I believe more features will be added. Thanks to the documentation and my experience creating a Telegram bot, I also learned how to create a Discord chatbot for the first time. If you find this chatbot helpful, don’t hesitate to add it to your community. If you find this chatbot helpful, don’t hesitate to add it to your community.

How I Built Technical Writer: An AI Chatbot For an Open Source Project using Coze

Building a Data Strategy: Aligning Data With Business Goals for Maximum Impact

iOS vs. Android Monetization: Why Not Understanding the Differences Could Harm Your Business

Authors:
(1) Guillaume Staerman, INRIA, CEA, Univ. Paris-Saclay, France;
(2) Marta Campi, CERIAH, Institut de l’Audition, Institut Pasteur, France;
(3) Gareth W. Peters, Department of Statistics & Applied Probability, University of California Santa Barbara, USA. Table of Links Abstract and 1. Introduction 2. Background & Preliminaries 2.1. Functional Isolation Forest 2.2. The Signature Method 3. Signature Isolation Forest Method 4. Numerical Experiments 4.1. Parameters Sensitivity Analysis 4.2. Advantages of (K-)SIF over FIF 4.3. Real-data Anomaly Detection Benchmark 5. Discussion & Conclusion, Impact Statements, and References Appendix A. Additional Information About the Signature B. K-SIF and SIF Algorithms C. Additional Numerical Experiments 2.2. The Signature Method The signature of a path is a sequence of iterated integrals that captures important information about the path’s geometric and topological features (Lyons et al., 2007; Fermanian, 2021). Furthermore, the signature of X is defined as the infinite collection of coordinate signature One may refer to Lee and Oberhauser (2023) for an account of the untruncated kernel signature. See also Section A in the Appendix for further details about the signature and its properties. This paper is available on arxiv under CC BY 4.0 DEED license. Authors: (1) Guillaume Staerman, INRIA, CEA, Univ. Paris-Saclay, France; (2) Marta Campi, CERIAH, Institut de l’Audition, Institut Pasteur, France; (3) Gareth W. Peters, Department of Statistics & Applied Probability, University of California Santa Barbara, USA. Authors: Authors: (1) Guillaume Staerman, INRIA, CEA, Univ. Paris-Saclay, France; (2) Marta Campi, CERIAH, Institut de l’Audition, Institut Pasteur, France; (3) Gareth W. Peters, Department of Statistics & Applied Probability, University of California Santa Barbara, USA. Table of Links Abstract and 1. Introduction Abstract and 1. Introduction 2. Background & Preliminaries 2. Background & Preliminaries 2.1. Functional Isolation Forest 2.1. Functional Isolation Forest 2.2. The Signature Method 2.2. The Signature Method 3. Signature Isolation Forest Method 3. Signature Isolation Forest Method 4. Numerical Experiments 4. Numerical Experiments 4.1. Parameters Sensitivity Analysis 4.1. Parameters Sensitivity Analysis 4.2. Advantages of (K-)SIF over FIF 4.2. Advantages of (K-)SIF over FIF 4.3. Real-data Anomaly Detection Benchmark 4.3. Real-data Anomaly Detection Benchmark 5. Discussion & Conclusion, Impact Statements, and References 5. Discussion & Conclusion, Impact Statements, and References Appendix A. Additional Information About the Signature A. Additional Information About the Signature B. K-SIF and SIF Algorithms B. K-SIF and SIF Algorithms C. Additional Numerical Experiments C. Additional Numerical Experiments 2.2. The Signature Method The signature of a path is a sequence of iterated integrals that captures important information about the path’s geometric and topological features (Lyons et al., 2007; Fermanian, 2021). Furthermore, the signature of X is defined as the infinite collection of coordinate signature Furthermore, the signature of X is defined as the infinite collection of coordinate signature X One may refer to Lee and Oberhauser (2023) for an account of the untruncated kernel signature. See also Section A in the Appendix for further details about the signature and its properties. This paper is available on arxiv under CC BY 4.0 DEED license. This paper is available on arxiv under CC BY 4.0 DEED license. available on arxiv

Unveiling Path Signatures: A Key to Geometric Insights in Data

Onthulling van padhandtekeninge: 'n Sleutel tot meetkundige insigte in data

Descubriendo las firmas de trayectoria: una clave para obtener información geométrica en los datos

Revelación de sinaturas de camiños: unha clave para coñecer os datos xeométricos

Mengungkap Tanda Jalur: Kunci Wawasan Geometris dalam Data

パスシグネチャの解明: データの幾何学的洞察への鍵

Жол қолтаңбаларын ашу: деректердегі геометриялық түсініктердің кілті

경로 서명 공개: 데이터에서 기하학적 통찰력의 열쇠

Famoahana sonia lalana: lakile ho an'ny fahitana geometrika amin'ny angona

د لارې لاسلیکونه افشا کول: په ډیټا کې د جیومیټریک بصیرت لپاره کلیدي

Kuzarura Nzira Masiginicha: Kiyi yeGeometric Insights muData

Zbulimi i nënshkrimeve të rrugës: Një çelës për njohuritë gjeometrike në të dhëna

راستے کے دستخطوں کی نقاب کشائی: ڈیٹا میں جیومیٹرک بصیرت کی کلید

From OpenAI to Closed AI: Custom Chips Are Closing The Doors—What’s Next? 

Ад OpenAI да закрытага AI: Карыстальніцкія мікрасхемы зачыняюць дзверы - што далей? 

De l'OpenAI a la IA tancada: els xips personalitzats estan tancant les portes: què passa? 

Von OpenAI zu Closed AI: Kundenspezifische Chips schließen die Türen – was kommt als Nächstes?

Από το OpenAI στο Closed AI: Τα προσαρμοσμένα τσιπ κλείνουν τις πόρτες—Τι ακολουθεί; 

De la IA abierta a la IA cerrada: los chips personalizados están cerrando las puertas. ¿Qué sigue?

Az OpenAI-tól a zárt mesterséges intelligenciaig: Az egyedi chipek bezárják az ajtókat – mi a következő lépés? 

Dari OpenAI ke AI Tertutup: Chip Kustom Menutup Pintu—Apa Selanjutnya?

OpenAI からクローズド AI へ: カスタム チップが扉を閉ざす — 次は何が起こるのか?

Kobanda na OpenAI tii na AI oyo ekangami: Ba puces personnalisées ezali kokanga ba portes —What’s Next? 

له OpenAI څخه تړل شوي AI ته: دودیز چپس دروازې بندوي — بیا څه دي؟ 

От открытого ИИ к закрытому ИИ: кастомные чипы закрывают двери — что дальше?

Від відкритого штучного інтелекту до закритого штучного інтелекту: спеціальні мікросхеми закривають двері — що далі? 

What is the Signature Isolation Forest? 

Authors:
(1) Yuwei Guo, The Chinese University of Hong Kong;
(2) Ceyuan Yang, Shanghai Artificial Intelligence Laboratory with Corresponding Author;
(3) Anyi Rao, Stanford University;
(4) Zhengyang Liang, Shanghai Artificial Intelligence Laboratory;
(5) Yaohui Wang, Shanghai Artificial Intelligence Laboratory;
(6) Yu Qiao, Shanghai Artificial Intelligence Laboratory;
(7) Maneesh Agrawala, Stanford University;
(8) Dahua Lin, Shanghai Artificial Intelligence Laboratory;
(9) Bo Dai, The Chinese University of Hong Kong and The Chinese University of Hong Kong. Table of Links Abstract and 1 Introduction 2 Work Related 3 Preliminary AnimateDiff 4.1 Alleviate Negative Effects from Training Data with Domain Adapter 4.2 Learn Motion Priors with Motion Module 4.3 Adapt to New Motion Patterns with MotionLora 4.4 AnimateDiff in Practice 5 Experiments and 5.1 Qualitative Results 5.2 Qualitative Comparison 5.3 Ablative Study 5.4 Controllable Generation 6 Conclusion 7 Ethics Statement 8 Reproducibility Statement, Acknowledgement and References 7 ETHICS STATEMENT We strongly condemn the misuse of generative AI to create content that harms individuals or spreads misinformation. However, we acknowledge the potential for our method to be misused since it primarily focuses on animation and can generate human-related content. It is also important to highlight that our method incorporates personalized text-to-image models developed by other artists. These models may contain inappropriate content and can be used with our method. To address these concerns, we uphold the highest ethical standards in our research, including adhering to legal frameworks, respecting privacy rights, and encouraging the generation of positive content. Furthermore, we believe that introducing an additional content safety checker, similar to that in Stable Diffusion (Rombach et al., 2022), could potentially resolve this issue. This paper is available on arxiv under CC BY 4.0 DEED license. Authors: (1) Yuwei Guo, The Chinese University of Hong Kong; (2) Ceyuan Yang, Shanghai Artificial Intelligence Laboratory with Corresponding Author; (3) Anyi Rao, Stanford University; (4) Zhengyang Liang, Shanghai Artificial Intelligence Laboratory; (5) Yaohui Wang, Shanghai Artificial Intelligence Laboratory; (6) Yu Qiao, Shanghai Artificial Intelligence Laboratory; (7) Maneesh Agrawala, Stanford University; (8) Dahua Lin, Shanghai Artificial Intelligence Laboratory; (9) Bo Dai, The Chinese University of Hong Kong and The Chinese University of Hong Kong. Authors: Authors: (1) Yuwei Guo, The Chinese University of Hong Kong; (2) Ceyuan Yang, Shanghai Artificial Intelligence Laboratory with Corresponding Author; (3) Anyi Rao, Stanford University; (4) Zhengyang Liang, Shanghai Artificial Intelligence Laboratory; (5) Yaohui Wang, Shanghai Artificial Intelligence Laboratory; (6) Yu Qiao, Shanghai Artificial Intelligence Laboratory; (7) Maneesh Agrawala, Stanford University; (8) Dahua Lin, Shanghai Artificial Intelligence Laboratory; (9) Bo Dai, The Chinese University of Hong Kong and The Chinese University of Hong Kong. Table of Links Abstract and 1 Introduction Abstract and 1 Introduction 2 Work Related 2 Work Related 3 Preliminary 3 Preliminary AnimateDiff AnimateDiff 4.1 Alleviate Negative Effects from Training Data with Domain Adapter 4.1 Alleviate Negative Effects from Training Data with Domain Adapter 4.2 Learn Motion Priors with Motion Module 4.2 Learn Motion Priors with Motion Module 4.3 Adapt to New Motion Patterns with MotionLora 4.3 Adapt to New Motion Patterns with MotionLora 4.4 AnimateDiff in Practice 4.4 AnimateDiff in Practice 5 Experiments and 5.1 Qualitative Results 5 Experiments and 5.1 Qualitative Results 5.2 Qualitative Comparison 5.2 Qualitative Comparison 5.3 Ablative Study 5.3 Ablative Study 5.4 Controllable Generation 5.4 Controllable Generation 6 Conclusion 6 Conclusion 7 Ethics Statement 7 Ethics Statement 8 Reproducibility Statement, Acknowledgement and References 8 Reproducibility Statement, Acknowledgement and References 7 ETHICS STATEMENT We strongly condemn the misuse of generative AI to create content that harms individuals or spreads misinformation. However, we acknowledge the potential for our method to be misused since it primarily focuses on animation and can generate human-related content. It is also important to highlight that our method incorporates personalized text-to-image models developed by other artists. These models may contain inappropriate content and can be used with our method. To address these concerns, we uphold the highest ethical standards in our research, including adhering to legal frameworks, respecting privacy rights, and encouraging the generation of positive content. Furthermore, we believe that introducing an additional content safety checker, similar to that in Stable Diffusion (Rombach et al., 2022), could potentially resolve this issue. This paper is available on arxiv under CC BY 4.0 DEED license. This paper is available on arxiv under CC BY 4.0 DEED license. available on arxiv

AnimateDiff Ethics Statement: Ensuring Responsible Use of Generative AI for Animation

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