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Meet the Winners of Startups in North and Central America

One of the hottest areas in technology today is machine learning. The rate of development from month to month is astonishing. Architectures are rapidly evolving, and can no longer keep pace. But what's even worse, Moore's Law itself is about to hit a wall. Moore's Law The essence of Moore's Law is that the number of transistors on integrated circuits approximately doubles every eighteen months. This trend has held for a long time, as technological advancements have enabled the production of ever-smaller and more efficient transistors. However, we've reached a physical limit where the laws of physics give us a reality check. Beyond a certain point, making smaller transistors is no longer possible. They don't work because electrons leak out of them. The only solution is to look for alternative architectures. One direction is the creation of specialized hardware, such as (Application-Specific Integrated Circuits). Recently, there was headline news about , a specialized processor designed specifically for large language models (LLMs). It is capable of running LLMs much faster and with much less energy consumption than traditional GPUs. Although this circuit is made with conventional technology, it is optimized for the task, which accounts for its significant speedup. Such specialized hardware can exploit the reserves in current technology, but the collision of Moore's Law with its limits also poses a constraint here. ASICs Groq's LPU The company Extropic came forward with a bolder idea. Their solution would banish transistors and replace them with something else. Like Google, the company was founded by two guys: and . Both worked in the field of quantum computing before founding the company, and their chip lies somewhere halfway between traditional integrated circuits and quantum computers. Guillaume Verdon Trevor McCourt As I mentioned before, the biggest limitation of traditional integrated circuits is that transistors cannot be miniaturized indefinitely. In very small domains, the rules of quantum mechanics significantly impact particles, making transistor operation impossible. In contrast, quantum computers leverage the effects of quantum mechanics. The greatest challenge with quantum computers is that qubits must be very well isolated from the environment. Even minimal noise can disrupt the system's operation. This is why quantum computers need to be cooled to absolute zero degrees to prevent the surrounding heat from interfering with their function. Extropic's brilliant idea is to, instead of fighting against environmental noise and heat, make use of them. This is where the term " " comes from. Thermodynamic computing In the field of machine learning, random noise is used extensively. One example of this is , which is also used by the Midjourney image generator. Here, a bit of noise is added to the image at every step until the entire image becomes noise. The neural network is then trained to reverse this process, that is, to generate an image from noise based on the given text. If the system is trained with enough images and text, it will be capable of generating images from random noise based on text. This is how Midjourney operates. normal distribution stable diffusion In fact, the use of noise is even more widespread. In any neural network, the initial weights are usually initialized with random noise. During training, shapes the final weights from this random noise. Thus, a similar process occurs in every neural network as in stable diffusion: the final model emerges from noise through the modification of weights during training. backpropagation On current computer architectures, this random distribution can only be emulated with circuits made of deterministic transistors. In contrast, Extropic's circuit does this in an analog manner. The starting state is completely random, normally distributed thermal noise. Through programming the circuit, this noise can be modified within each component. Instead of transistors, analog weights take their place, which are noisy, but the outcome can be determined through statistical analysis of the output. The guys call this . probabilistic computing These analog circuits are much faster and consume much less energy, and since the thermal noise is not only non-disruptive but actually an essential component of the operation, they do not require the special conditions needed by quantum computers. The chips can be manufactured with existing production technology, so they could enter the commercial market within a few years. As we have seen from the above, Extropic's technology is very promising. However, what personally piqued my interest is that it is more biologically plausible. Of course, I don't think that the neurons in artificial neural networks have anything to do with human brain neurons. These are two very different systems. However, it is clear that the human brain does not learn through . Biological learning is something entirely different, and randomness certainly plays a significant role in it. gradient descent In fact, in biology and nature, everything operates randomly. What we see as deterministic at a high level is actually just what statistically stands out from many random events. This is how, for example, many living beings (including us humans) came to be through completely random evolution yet are built with almost engineering precision. I suspect that the human brain operates in a similar way to evolution. A multitude of random events within a suitably directed system, which we perceive from the outside as consistent thinking. This is why , and now I see the same principle in Extropic's chip. genetic algorithms were so intriguing to me If you are interested, check the or with the founder guys. company homepage this interview

Thermodynamic Computing: How to Save Machine Learning by Replacing Transistors

Psychology of the Unconscious by C. G. Jung, is part of the HackerNoon Books Series. You can jump to any chapter in this book . TRANSLATOR’S NOTE here TRANSLATOR’S NOTE That humanity is seeking a new message, a new light upon the meaning of life, and something tangible, as it were, with which it can work towards a larger understanding of itself and its relation to the universe, is a fact I think none will gainsay. Therefore, it has seemed to me particularly timely to introduce to the English-speaking world Dr. Jung’s remarkable book, “Wandlungen und Symbole der Libido.” In this work he has plunged boldly into the treacherous sea of mythology and folklore, the productions of the ancient mind and that of the common people, and turned upon this vast material the same scientific and painstaking method of psychologic analysis that is applied to the modern mind, in order to reveal the common bond of desire and longing which unites all humanity, and thus bridge the gaps presumed to exist between ancient and widely separated peoples and those of our modern time. The discovery of this undercurrent affecting and influencing ancient peoples as well as modern serves as a foundation or platform from which he proceeds to hold aloft a new ideal, a new goal of attainment possible of achievement and which can be intellectually satisfying, as well as emotionally appealing: the goal of . moral autonomy This book, remarkable for its erudition and the tremendous labor expended upon it, as well as for the new vilight which it sheds upon human life, its motives, its needs and its possibilities, is not one for desultory reading or superficial examination. Such an approach will prevent the reader from gaining anything of its real value; but for those who can bring a serious interest and willingness to give a careful study to it the work will prove to be a veritable mine capable of yielding the greatest riches. The difficulties in translating a book such as this are almost insuperable, but I have tried faithfully to express Dr. Jung’s thought, keeping as close to the original text as possible and, at the same time, rendering the difficult material and complicated German phrasing as simply and clearly as the subject-matter would allow. In all this work I owe much to Miss Helen I. Brayton, without whose faithful assistance the work would never have been completed. I wish to acknowledge my gratitude to Mr. Louis Untermeyer, whose help in rendering the poetic quotations into English verse has been invaluable, and to express as well my gratitude to other friends who have assisted me in various ways from time to time. B. M. H. New York, 1915. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. C. G. Jung (2021). Psychology of the Unconscious. Urbana, Illinois: Project Gutenberg. Retrieved https://www.gutenberg.org/cache/epub/65903/pg65903-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at , located at . www.gutenberg.org https://www.gutenberg.org/policy/license.html

TRANSLATOR’S NOTE

is part of HackerNoon’s Book Blog Post series. You can jump to any chapter in this book here: . Translator's Preface. Crime and Punishment, by Fyodor Dostoyevsky [LINK TO TABLE OF LINK] TRANSLATOR’S PREFACE About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. A few words about Dostoevsky himself may help the English reader to understand his work. Dostoevsky was the son of a doctor. His parents were very hard-working and deeply religious people, but so poor that they lived with their five children in only two rooms. The father and mother spent their evenings in reading aloud to their children, generally from books of a serious character. Though always sickly and delicate Dostoevsky came out third in the final examination of the Petersburg school of Engineering. There he had already begun his first work, “Poor Folk.” This story was published by the poet Nekrassov in his review and was received with acclamations. The shy, unknown youth found himself instantly something of a celebrity. A brilliant and successful career seemed to open before him, but those hopes were soon dashed. In 1849 he was arrested. Though neither by temperament nor conviction a revolutionist, Dostoevsky was one of a little group of young men who met together to read Fourier and Proudhon. He was accused of “taking part in conversations against the censorship, of reading a letter from Byelinsky to Gogol, and of knowing of the intention to set up a printing press.” Under Nicholas I. (that “stern and just man,” as Maurice Baring calls him) this was enough, and he was condemned to death. After eight months’ imprisonment he was with twenty-one others taken out to the Semyonovsky Square to be shot. Writing to his brother Mihail, Dostoevsky says: “They snapped words over our heads, and they made us put on the white shirts worn by persons condemned to death. Thereupon we were bound in threes to stakes, to suffer execution. Being the third in the row, I concluded I had only a few minutes of life before me. I thought of you and your dear ones and I contrived to kiss Plestcheiev and Dourov, who were next to me, and to bid them farewell. Suddenly the troops beat a tattoo, we were unbound, brought back upon the scaffold, and informed that his Majesty had spared us our lives.” The sentence was commuted to hard labour. One of the prisoners, Grigoryev, went mad as soon as he was untied, and never regained his sanity. The intense suffering of this experience left a lasting stamp on Dostoevsky’s mind. Though his religious temper led him in the end to accept every suffering with resignation and to regard it as a blessing in his own case, he constantly recurs to the subject in his writings. He describes the awful agony of the condemned man and insists on the cruelty of inflicting such torture. Then followed four years of penal servitude, spent in the company of common criminals in Siberia, where he began the “Dead House,” and some years of service in a disciplinary battalion. He had shown signs of some obscure nervous disease before his arrest and this now developed into violent attacks of epilepsy, from which he suffered for the rest of his life. The fits occurred three or four times a year and were more frequent in periods of great strain. In 1859 he was allowed to return to Russia. He started a journal—“Vremya,” which was forbidden by the Censorship through a misunderstanding. In 1864 he lost his first wife and his brother Mihail. He was in terrible poverty, yet he took upon himself the payment of his brother’s debts. He started another journal—“The Epoch,” which within a few months was also prohibited. He was weighed down by debt, his brother’s family was dependent on him, he was forced to write at heart-breaking speed, and is said never to have corrected his work. The later years of his life were much softened by the tenderness and devotion of his second wife. In June 1880 he made his famous speech at the unveiling of the monument to Pushkin in Moscow and he was received with extraordinary demonstrations of love and honour. A few months later Dostoevsky died. He was followed to the grave by a vast multitude of mourners, who “gave the hapless man the funeral of a king.” He is still probably the most widely read writer in Russia. In the words of a Russian critic, who seeks to explain the feeling inspired by Dostoevsky: “He was one of ourselves, a man of our blood and our bone, but one who has suffered and has seen so much more deeply than we have his insight impresses us as wisdom... that wisdom of the heart which we seek that we may learn from it how to live. All his other gifts came to him from nature, this he won for himself and through it he became great.” About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Urbana, Illinois: Project Gutenberg. Retrieved April 2022, from Fyodor Dostoyevsky. 2001. CRIME AND PUNISHMENT. https://www.gutenberg.org/files/2554/2554-h/2554-h.htm#link2HCH0016 This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever.  You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at , located at . www.gutenberg.org https://www.gutenberg.org/policy/license.html

Crime and Punishment: Translator's Preface

The Interpretation of Dreams by Sigmund Freud, is part of the HackerNoon Books Series. You can jump to any chapter in this book here . TRANSLATOR’S PREFACE TRANSLATOR’S PREFACE Since the appearance of the author’s Selected Papers on Hysteria and other Psychoneuroses, and Three Contributions to the Sexual Theory, much has been said and written about Freud’s works. Some of our readers have made an honest endeavour to test and utilise the author’s theories, but they have been handicapped by their inability to read fluently very difficult German, for only two of Freud’s works have hitherto been accessible to English readers. For them this work will be of invaluable assistance. To be sure, numerous articles on the Freudian psychology have of late made their appearance in our literature; but these scattered papers, read by those unacquainted with the original work, often serve to confuse rather than enlighten. For Freud cannot be mastered from the reading of a few pamphlets, or even one or two of his original works. Let me repeat what I have so often said: No one is really qualified to use or to judge Freud’s psychoanalytic method who has not thoroughly mastered his theory of the neuroses—The Interpretation of Dreams, Three Contributions to the Sexual Theory, The Psychopathology of Everyday Life, and Wit and its Relation to the Unconscious, and who has not had considerable experience in analysing the dreams and psychopathological actions of himself and others. That there is required also a thorough training in normal and abnormal psychology goes without saying. The Interpretation of Dreams is the author’s greatest and most important work; it is here that he develops his psychoanalytic technique, a thorough knowledge of which is absolutely indispensable for every worker in this field. The difficult task of making a translation of this work has, therefore, been xiiundertaken primarily for the purpose of assisting those who are actively engaged in treating patients by Freud’s psychoanalytic method. Considered apart from its practical aim, the book presents much that is of interest to the psychologist and the general reader. For, notwithstanding the fact that dreams have of late years been the subject of investigation at the hands of many competent observers, only few have contributed anything tangible towards their solution; it was Freud who divested the dream of its mystery, and solved its riddles. He not only showed us that the dream is full of meaning, but amply demonstrated that it is intimately connected with normal and abnormal mental life. It is in the treatment of the abnormal mental states that we must recognise the most important value of dream interpretation. The dream does not only reveal to us the cryptic mechanisms of hallucinations, delusions, phobias, obsessions, and other psychopathological conditions, but it is also the most potent instrument in the removal of these. I take this opportunity of expressing my indebtedness to Professor F. C. Prescott for reading the manuscript and for helping me overcome the almost insurmountable difficulties in the translation. A. A. BRILL. New York City. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Sigmund Freud (2021). The Interpretation of Dreams. Urbana, Illinois: Project Gutenberg. Retrieved October 2022 https://www.gutenberg.org/cache/epub/66048/pg66048-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at www.gutenberg.org , located at https://www.gutenberg.org/policy/license.html.

TRANSLATOR’S PREFACE

Totem and Taboo by Sigmund Freud, is part of the HackerNoon Books Series. You can jump to any chapter in this book here . TRANSLATOR’S INTRODUCTION TRANSLATOR’S INTRODUCTION When one reviews the history of psychoanalysis one finds that it had its inception in the study of morbid mental states. Beginning with the observation of hysteria and the other neuroses Professor Freud gradually extended his investigations to normal psychology and evolved new concepts and new methods of study. The neurotic symptoms were no longer imaginary troubles the nature of which one could not grasp, but were conceived as mental and emotional maladjustments to one’s environment. The stamp of degeneracy impressed upon neurotics by other schools of medicine was altogether eradicated. Deeper investigation showed conclusively that a person might become neurotic if subjected to certain environments, and that there was no definite dividing line between normal and abnormal. The hysterical symptoms, obsessions, doubts, phobias, as well as hallucinations of the insane, show the same mechanisms as those similar psychic structures which one constantly encounters in normal persons in the form of mistakes in talking, reading, writing, forgettin, dreams and wit. The dream, always highly valued by the populace, and as much despised by the educated classes, has a definite structure and meaning when subjected to analysis. Professor Freud’s monumental work, The Interpretation of Dreams , marked a new epoch in the history of mental science. One might use the same words in reference to his profound analysis of wit Faulty psychic actions, dreams and wit are products of the unconscious mental activity, and like neurotic or psychotic manifestations represent efforts at adjustment to one’s environment. The slip of the tongue shows that on account of unconscious inhibitions the individual concerned is unable to express his true thoughts; the dream is a distorted or plain expression of those wishes which are prohibited in the waking states, and the witticism, owing to its veiled or indirect way of expression, enables the individual to obtain pleasure from forbidden sources. But whereas dreams, witticisms, and faulty actions give evidences of inner conflicts which the individual overcomes, the neurotic or psychotic symptom is the result of a failure and represents a morbid adjustment. The aforementioned psychic formations are therefore nothing but manifestations of the struggle with reality, the constant effort to adjust one’s primitive feelings to the demands of civilization. In spite of all later development the individual retains all his infantile psychic structures. Nothing is lost; the infantile wishes and primitive impulses can always be demonstrated in the grown-up and on occasion can be brought back to the surface. In his dreams the normal person is constantly reviving his childhood, and the neurotic or psychotic individual merges back into a sort of psychic infantilism through his morbid productions. The unconscious mental activity which is made up of repressed infantile material for ever tries to express itself. Whenever the individual finds it impossible to dominate the difficulties of the world of reality there is a regression to the infantile, and psychic disturbances ensue which are conceived as peculiar thoughts and acts. Thus the civilized adult is the result of his childhood or the sum total of his early impressions; psychoanalysis thus confirms the old saying: The child is father to the man. It is at this point in the development of psychoanalysis that the paths gradually broadened until they finally culminated in this work. There were many indications that the childhood of the individual showed a marked resemblance to the primitive history or the childhood of races. The knowledge gained from dream analysis and phantasies , when applied to the productions of racial phantasies, like myths and fairy tales, seemed to indicate that the first impulse to form myths was due to the same emotional strivings which produced dreams, fancies and symptoms . Further study in this direction has thrown much light on our great cultural institutions, such as religion, morality, law and philosophy, all of which Professor Freud has modestly formulated in this volume and thus initiated a new epoch in the study of racial psychology. [7] [8] I take great pleasure in acknowledging my indebtedness to Mr Alfred B. Kuttner for the invaluable assistance he rendered in the translation of this work. A. A. BRILL. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Sigmund Freud (2021). Totem and Taboo. Urbana, Illinois: Project Gutenberg. Retrieved October 2022 https://www.gutenberg.org/cache/epub/41214/pg41214-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at www.gutenberg.org , located at https://www.gutenberg.org/policy/license.html.

TRANSLATOR’S INTRODUCTION

Nvidia's annual developer conference in 2024, known as GTC (GPU Technology Conference), was a pivotal event that unveiled groundbreaking advancements in artificial intelligence (AI) chips, software tools, and strategic partnerships. The conference, led by Nvidia's CEO Jensen Huang, showcased the company's commitment to innovation and leadership in the tech industry. And if you want to understand the latest trends from the world of AI - subscribe to my newsletter ‘ ‘. And the best part - it’s completely free! AI Hunters Now, onto the key takeaways from Nvidia's GTC 2024: Flagship AI Chip - B200 "Blackwell" The Flagship AI Chip - B200 "Blackwell" unveiled by Nvidia at GTC 2024 represents a groundbreaking advancement in AI chip technology. Named after mathematician David Blackwell, this new chip is a significant leap forward in performance, being 30 times faster than its predecessor, the Hopper series, particularly excelling at tasks like supporting advanced chatbots and large language models. With an impressive 208 billion transistors, more than double the previous chip, the B200 chip offers exceptional processing power. Despite its remarkable performance, the B200 chip is designed with efficiency in mind, using 25 times less energy and money than the previous Hopper series. This focus on efficiency not only enhances its cost-effectiveness but also positions it as a sustainable solution for AI applications. The innovative design of the B200 chip, which combines two squares of silicon into a single chip, allows all transistors to access memory simultaneously, further boosting productivity and performance. Nvidia's dominance in the data center AI chip market, with a market share of roughly 80%, underscores the significance of the B200 chip in shaping the future of AI technology. Major tech giants like Amazon, Google, Meta Platforms, Microsoft, OpenAI, and Tesla are expected to adopt this new chip, highlighting its importance and impact in the industry. Expected to hit the market later in 2024, the B200 chip offers advanced capabilities for AI applications. With its powerful performance, energy efficiency, and anticipated industry-wide adoption, the Blackwell B200 chip is poised to redefine AI processing and drive innovation across various sectors. Points to Reflect Upon: Performance Leap: Consider the implications of the B200 chip's 30x performance increase for AI applications and industries. Assess the feasibility of integrating the B200 chip into existing AI infrastructure for enhanced performance. Efficiency Benefits: Conduct a cost-benefit analysis to determine the potential savings from transitioning to the B200 chip. Software Tools for AI Integration Nvidia Inference Microservices (NIM) introduced at GTC 2024 represent a significant advancement in AI deployment technology. NIM is a cloud-native microservices solution that simplifies the development and deployment of generative AI applications across various infrastructures, including cloud, data centers, and GPU-accelerated workstations. It offers a streamlined path for developing AI-powered enterprise applications and deploying AI models in production, aiming to shorten time-to-market and simplify deployment processes for organizations transitioning to full-scale production deployments. NIM is designed to bridge the gap between the complexities of AI model development and the operational needs of enterprises, enabling a broader pool of developers to contribute to AI transformations within their companies. Some core benefits of NIM include its portability and control, allowing model deployment across various infrastructures, from local workstations to cloud environments. It provides prebuilt containers and Helm charts with optimized models validated across different NVIDIA hardware platforms, cloud service providers, and Kubernetes distributions, ensuring support across all NVIDIA-powered environments. Developers can access AI models through industry-standard APIs, simplifying the development of AI applications and enabling swift updates within the ecosystem. NIM also addresses the need for domain-specific solutions by packaging domain-specific NVIDIA CUDA libraries and specialized code tailored to various domains like language, speech, video processing, healthcare, and more. Leveraging optimized inference engines for each model and hardware setup, NIM ensures the best possible latency and throughput on accelerated infrastructure, reducing the cost of running inference workloads as they scale and enhancing the end-user experience. Part of the NVIDIA AI Enterprise suite, NIM is built with an enterprise-grade base container, providing a solid foundation for enterprise AI software through rigorous validation, enterprise support, and regular security updates. With support for various AI models, including community models, NVIDIA AI Foundation models, and custom AI models, NIM simplifies the AI model deployment process by packaging algorithmic, system, and runtime optimizations and adding industry-standard APIs. This comprehensive solution accelerates the deployment of scalable and customized AI applications in production, making AI more accessible and customizable across industries. Points to Reflect Upon: Business Impact: Consider how NIM can empower businesses to harness AI capabilities and drive innovation. Operational Efficiency: Evaluate how enhanced system efficiency can optimize business processes and decision-making. Strategic Partnerships and Collaborations Nvidia's expanded partnerships with industry leaders and software makers announced at GTC 2024 mark a significant milestone in the development of AI technologies and their integration into various sectors. These collaborations highlight Nvidia's strategic efforts to advance AI infrastructure, enhance AI capabilities, and drive innovation across industries. One key partnership involves Microsoft, where Nvidia and Microsoft are working together to bring the power of Nvidia Grace Blackwell GB200 and advanced Nvidia technologies to Azure. This collaboration aims to deliver trillion-parameter foundation models for tasks like natural language processing, computer vision, speech recognition, and more. Additionally, Microsoft is introducing the Azure NC H100 v5 VM virtual machine based on the Nvidia H100 NVL platform to cater to midrange training and inferencing needs. Furthermore, Nvidia's inference microservices are being integrated into Azure, enhancing AI capabilities for users by providing cloud-native microservices for optimized inference on various foundation models. This integration streamlines AI deployments and accelerates the development of performance-optimized production AI applications. In the automotive sector, Nvidia has deepened its ties with leading Chinese automakers like BYD, Xpeng, GAC Aion's Hyper brand, Zeekr, and Li Auto. These partnerships focus on integrating Nvidia's cutting-edge technologies, such as the Drive Thor in-vehicle chips, to enhance autonomous driving capabilities and infotainment systems in vehicles. Collaborations with US-based software company Cerence aim to adapt large language model AI systems for in-car applications, promising advanced voice command systems and improved user experiences. Overall, these partnerships unveiled at GTC 2024 demonstrate Nvidia's commitment to driving innovation across various industries by leveraging cutting-edge technologies and fostering collaborations with industry leaders and software makers. Points to Reflect Upon: Industry Impact: Consider how partnerships with key players can influence the adoption and integration of Nvidia's technology in various sectors. Innovation Potential: Reflect on the potential for collaborative efforts to drive innovation and create new opportunities in AI and technology. Focus on Sustainability and Sovereign AI Nvidia's emphasis on sustainability and sovereign AI initiatives at GTC 2024 underscores the company's commitment to responsible technology development. The focus on addressing environmental concerns related to AI training and data center energy consumption demonstrates Nvidia's proactive stance on sustainability issues. By prioritizing energy efficiency and sustainable practices in AI development, Nvidia is setting a standard for responsible innovation in the tech industry. Furthermore, Nvidia's dedication to sovereign AI initiatives, which enable nations to produce AI using their infrastructure and workforce, highlights the company's commitment to promoting ethical and secure AI practices globally. By empowering countries to develop AI capabilities locally, Nvidia is fostering digital sovereignty and supporting economic growth while ensuring data protection and security. Overall, Nvidia's dual focus on sustainability and sovereign AI at GTC 2024 showcases the company's holistic approach to technology development, balancing innovation with ethical considerations and environmental responsibility. This strategic emphasis on sustainability and sovereignty sets Nvidia apart as a leader in responsible AI practices and underscores its commitment to shaping a more sustainable and secure future for AI technologies. Points to Reflect Upon: Environmental Responsibility: Consider the implications of Nvidia's sustainability efforts on the tech industry and environmental conservation. Develop a sustainability strategy to align with Nvidia's initiatives. Ethical AI Practices: Reflect on the importance of promoting ethical AI practices and ensuring transparency in AI development. Global Engagement: Explore opportunities for global engagement to promote sovereign AI practices and support technological independence. Market Position and Future Outlook Nvidia's strong market position and future outlook were prominently highlighted at GTC 2024, emphasizing the company's leadership in GPU technology and AI innovation amidst competition from rivals like AMD, Intel, and emerging startups. Announcements at GTC 2024 regarding new products such as the Blackwell GPU series, DGX GB200 System, and DGX SuperPOD underscore Nvidia's focus on advancing AI infrastructure and enabling next-generation AI models. This strategic vision positions Nvidia at the forefront of technological advancements that will shape the future of AI computing and high-performance computing (HPC). Overall, Nvidia's market position and future outlook at GTC 2024 highlight its resilience, innovation drive, and strategic vision for continued growth and leadership in the evolving landscape of AI technologies. To sum up, Nvidia's annual developer conference in 2024 was a platform for unveiling cutting-edge AI technology, software tools, and strategic partnerships that reinforce the company's position as a leader in the tech industry. The key takeaways from GTC 2024 underscore Nvidia's commitment to innovation, sustainability, and collaboration, setting the stage for continued advancements in AI, GPU technology, and high-performance computing. P.S. Check out some of my previous articles at HackerNoon: Google Introduces Gemma: Revolutionary Access to Pre-Trained AI Models Sora's AI Innovation Set to Disrupt Video Content Creation Breaking Down the Next Big Thing in NFTs: ERC-404 Spotlight Gemini 1.5 Unleashes Unprecedented Context for AI Applications The AI Revolution in Journalism: A New Era of Enhanced Reporting DeFi Community Building: A Step-by-Step Guide for Crypto Startups

Nvidia GPU Technology Conference In 2024: A Deep-Dive 

Artificial intelligence gives humanity tremendous opportunities. With that, great risks. We celebrate online translators, amicable chatbots, well-drawing neural networks, and robot vacuum cleaners. We jubilate everything that makes life easier — not to mention scientific achievements. That said, we seem to be afraid of AI. But why? Is it even justified? Let's find out. First Steps in AI The first research on AI began in the 1930s. At that time, AI was already deemed a computer program able to perform tasks and learn. In 1927, an engineer of the Westinghouse Electric and Manufacturing Company, engineered the first humanoid robot, Herbert Televox. Roy Wensley It was programmed to answer calls and execute simple commands. Imagine you call home and ask Televox whether the lights are turned off! Or you can request to preheat dinner in the oven, and the robot will turn it on remotely. All that in 1927! Rise of AI: Dartmouth Conference The term artificial intelligence was first used in 1956, at the , New Hampshire. At the conference, scientists discussed many areas of AI application, from vision, learning, and research to language, gaming, and human interactions with robots. Dartmouth Conference in Hanover Since then, the golden age of AI has started. Artificial intelligence has become the official field of science. AI robots could solve specific tasks. For more accomplished versions, a bigger computing capacity was necessary. Not So Positive AI: Intelligence Explosion The number of robots — from a vacuum cleaner to a smart kettle — used in daily life was growing. Researchers tried to predict the further flow of things. In 1966, British mathematician Good in his work ‘Speculations Concerning the First Ultraintelligent Machine’ formulated the principle of technological singularity, or intelligence explosion. Irving John According to this phenomenon, “ultraintelligent machine could design even better machines; there would then unquestionably be the ‘intelligence explosion,’ and the intelligence of man would be left far behind. Thus the first ultraintelligent machine is the last invention that man need ever make.” This work caused a great discussion in society and led to ethical concerns: Is it safe to interact with machines? Where are the boundaries of interactions? Who controls robots? Trade-Offs: Asimov’s Laws of Robotics One of the most famous solutions to the problem was proposed by the American writer and professor of biochemistry in 1942. In Asimov’s story ‘Runaround,’ he outlined the three Laws of Robotics: Isaac Asimov A robot may not injure a human being or, through inaction, allow a human being to come to harm. A robot must obey the orders given to it by human beings, except where such orders would conflict with the First Law. A robot must protect its own existence as long as such protection does not conflict with the First or Second Laws. But, many years later, these postulates remained fiction and became the ground for future doubts, fears, and frightening scenarios. Where Does the Fear Come From? In the 1990s, neural networks became a real breakthrough. They could collect data, form experiences, analyze the received information, and draw conclusions at much higher speeds. Since there were more precise and less provocative definitions for modern technologies, the phrase artificial intelligence lost its relevance. John McCarthy, an American computer and cognitive scientist, said, ‘As soon as it works, no one calls it AI anymore." It is human nature to be scared of the new — the law of survival in action. Artificial intelligence provokes a defensive reaction. But it’s not the AI itself that frightens us. It’s the fear of the unknown. Many do not understand artificial intelligence, its processes and its consequences. People are also scared lest artificial intelligence replace them at work. Here also comes media. In movies, books, and media, AI is often an evil genius who wants to destroy humanity. At the same time, there are many stories of human interaction with technology: Self-realization through a robot (the movie ‘Real Steel’); Complete suppression of human will by a machine (the picture ‘Upgrade’); Use of technology for good (Iron Man's virtual assistant Jarvis); Capture of the world by intelligent machines (the movie ‘Terminator’ or the ‘Matrix’ trilogy). Smart machines appeared in fantasy long before they did in real. The word ‘robot’ was first used in the science-fiction play R.U.R. by in 1920. Čapek’s robots were very close to the modern perception of androids. Karel Čapek People view AI as a living organism capable of evoking feelings, if not to replace a person. We can see that in the picture ‘Her.’ Moreover, we no longer perceive technologies like Siri, Mercedes, or chatbots as AI. However advanced, machines do not have a nervous system. Even a perfectly accurate emulation of the human brain in an electronic version cannot make a robot feel and empathize. Mikalai Dzisko*, Senior Editor at , says:* Ocean Power ‘Journalists also distort the image of neural networks and artificial intelligence. Instead of educating their audience and showing them how to use the neural network, they mouse around for intolerance and unethical behavior in ChatGPT. Will it write the f-word? When will it offend a user? Is it possible to bring it into conflict? How many genders does the neural network admit? These questions blur the reputation and essence of the technology. Will the Fear Of AI Disappear? Despite widespread fear, some movies, books, and people support a positive reputation of neural networks: In the 1990’s sci-fi picture ‘Total Recall,’ AI helps the main character to investigate crimes on Mars; In the Mass Effect computer games, you can’t win without AI; In the science fiction series ‘Black Mirror,’ artificial intelligence is sometimes represented as a positive character: in one of the episodes, it helps people find the perfect match — the utopian Tinder of the future. Artificial intelligence is often mentioned in gender studies. One of the most famous feminists of the last century, Donna Haraway, believed that cyborgization would help overcome binary, with all the ensuing problems and stereotypes. Today, human rights defenders are moving on. The non-profit organization raises the questions of people who can already be called cyborgs. Cyborg Foundation Its co-founder, artist Neil Harbisson, calls himself the first cyborg in the world because he implanted a special antenna in his skull that converts light waves into sound. ‘Should they have a license to use the technology? Their international law? What should cyborg insurance look like? Who will protect the civil liberties and inviolability of cyborg bodies?’ asks Eliezer Yudkowsky, co-founder and research fellow at the Machine Intelligence Research  Institute Stephen Hawking made a huge contribution to the popularization of the thesis ‘Technology is man's best friend.’ The famous physicist and cosmologist publicly spoke in favor of research and the development of artificial intelligence. Hawking believed that, with proper use, AI can help people solve many global problems. By personal example, he showed that a serious illness is no longer an obstacle to active scientific and public activity the moment you let technology into your life and body. Transhumanism VS. Posthumanism Transhumanists preach that the main task of a person is to improve the quality of their own life and overcome illness and death. Technology should be the best helper in this process. Cyborgization, regenerative medicine, various digital practices — virtual reality, metaverses — all this should make a person happy. Sounds defiant, doesn’t it? On the other hand, technology has been simplifying our lives for a long time. We just do not notice it: cars, microwaves, phones, the Internet, search engines, and so on. There is also a more radical approach, posthumanism. This philosophy is based on the consideration that man has reached the peak of their evolution in the Darwinian understanding and, to reach the next level; it is necessary not just to apply the product of his intellectual activity, but to directly implement it into life: to implant a chip in the brain to improve vision or hearing. This can also include biohacking, improving health indicators with the help of medicines, a proper lifestyle, and, of course, technologies, such as chips that read blood pressure, temperature, and sugar levels. Not the treatment of diseases, but the upgrade of the body and its own capabilities. Three Whales of Transhumanism Both trends are mostly theoretical, but the three main ideas of transhumanism seem intriguing. The first is super longevity. The belief that life is finite, and even more so limited by a conditional century, is a cultural stereotype that forces a person to distribute events within the time allotted to a human: to get married before the age of 25, to give birth before 30, to reach success before 45. What if you imagine that life is 200, or even 250 years? How will our attitude towards the time change? To your own health and biological age? What if we don't rush, try to do more, and adjust our lifestyle to this idea? A second duty of a transhuman is to raise the standard of living by reducing stress. Stress has become the main disease of the 21st century, the primary source of other problems and illnesses. A high standard of living is not only material goods, it is primarily harmony with oneself. This is what transhumanism adherers suggest to focus on. The third thesis of transhumanism is as follows: a person must combine the abilities of the brain and technology. Disturbing, right? In fact, we have been delegating some brain functions to neural networks for a long time: memory, sensory organs, and biological clocks, to name a few. We get up on the alarm clock, we do not waste time trying to remember the actor's name, we trust the route suggested by the navigator — and we are unlikely to follow it on our own. The neural network helps eliminate some processes, change our needs, reduce the time for completing tasks, and manage to do the important ones. Is It Even Possible? In theory, it is possible to achieve superintelligence by combining the capabilities of the human brain and a computer. Special implants could stimulate brain function, allow you to access the Internet, and interact with computers or other implant carriers. Today, such technologies are used only for medical purposes. For example, scientists at have developed implants that can stimulate individual parts of the brain with the help of electrical impulses and thus help address depression or Parkinson's disease. Stanford University All these utopian developments can inspire or make you think about improving your life. In the fight against AI anxiety, you just need to start. The first piece of advice unanimously given by those who work with neural networks is to stop calling this technology artificial intelligence. Intelligence — the defining characteristic between a human and an animal — remains man's main strength. There are no competitors on the horizon so far.

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