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Everything of Thought (XOT)

As illogical language models continue to progressively impact every part of our lives, Microsoft has revealed a strategy to make AI reason better, termed Everything of Thought (XOT). This approach was motivated by Google DeepMinds AlphaZero, which achieves competitive performance with extremely small neural networks.

East China Normal University and Georgia Institute of Technology worked together to create the new XOT technique. They employed a combination of well-known successful strategies for making difficult decisions, such as reinforcement learning and Monte Carlo Tree Search (MCTS).

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Researchers claim that by combining these methods, language models may more effectively generalize to novel scenarios. Experiments by the researchers on hard problems including the Game of 24, the 8-Puzzle, and the Pocket Cube showed promising results. When compared to alternative approaches, XOT has shown superior in solving previously intractable issues. There are, of course, limits to this supremacy. The system, despite its achievements, has not attained a level of 100% dependability.

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However, the study team thinks the framework is a good way to bring in outside knowledge for linguistic model inference. They are certain that it boosts performance, efficiency, and adaptability all at once, which is not possible with other approaches.

Researchers are looking at games as a potential next step in incorporating language models since current models can create sentences with outstanding precision but lack a key component of human-like thinking: the capacity to reason.

Academics have been looking at this for quite some time. The scholarly and technological community has spent years delving deeply into this mystery. However, despite their efforts to supplement AI with more layers, parameters, and attention methods, a solution remains elusive. Multimodality research has also been conducted, although thus far, it has not yielded any particularly promising or cutting-edge results.

We all know how terrible ChatGPT was at arithmetic when it was published, but earlier this year a team from Virginia Tech and Microsoft created a method called Algorithm of Thoughts (AoT) to enhance AIs algorithmic reasoning. It also hinted that by using this training strategy, huge language models might eventually be able to use their intuition in conjunction with optimized search to provide more accurate results.

A little over a month ago, Microsoft also investigated the moral justifications used by these models. As a result, the group suggested a revised framework to gauge its capacity for forming moral judgments. The 70-billion-parameter LlamaChat model fared better than its bigger rivals in the end. The findings ran counter to the conventional wisdom that more is better and the communitys dependence on large values for key metrics.

Microsoft looks to be taking a cautious approach to advancement while the large internet companies continue to suffer the repercussions of their flawed language models. They are taking it slow and steady with the addition of complexity to their models.

The XOT technique has not been announced for inclusion in any Microsoft products. Meanwhile, Google DeepMind CEO Demis Hassabis indicated in an interview that the company is exploring incorporating ideas inspired by AlphaGo into its Gemini project.

Metas CICERO, named for the famous Roman orator, also joined the fray a year ago, and its impressive proficiency in the difficult board game Diplomacy raised eyebrows among the AI community. Because it requires not only strategic thinking but also the ability to negotiate, this game has long been seen as an obstacle for artificial intelligence. CICERO, however, showed that it could handle these situations since it was able to hold sophisticated, human-like discussions. Considering the standards established by DeepMind, this finding was not ignored. The research team in the UK has long advocated for the use of games to train neural networks.

Their successes with AlphaGo set a high standard, which Meta matched by taking a page from DeepMinds playbook and fusing strategic thinking algorithms (like AlphaGos) with a natural language processing model (GPT-3). Because an AI agent playing Diplomacy requires not just knowledge of the rules and strategies of the game, but also an accurate assessment of the likelihood of treachery by human opponents, Metas model stood out. As Meta continues to develop Llama-3, this agent is the greatest alternative because of its capacity to carry on conversations with people using natural-sounding language. Metas larger AI programs, including CICERO, may herald the arrival of conversational AI.

[To share your insights with us, please write tosghosh@martechseries.com]

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Microsoft's LLM 'Everything Of Thought' Method Improves AI ... - AiThority

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In the ever-evolving world of technology, one can hardly keep track of the pace at which advancements occur. In every industry, from healthcare to entertainment, technology is causing sweeping changes, redefining traditional norms, and enhancing efficiency on an unprecedented scale. This is an exploration of just a few of these innovating technological advancements that are defining the future.

Artificial Intelligence (AI), already disruptive in its impact, continues to push barriers. With the introduction of advanced systems such as GPT-3 by OpenAI or DeepMinds AlphaGo, the world is witnessing AIs potential in generating human-like text, accurate predictions, problem-solving and strategy development. Companies are reaping the benefits of AI, including improved customer service and streamlined operational processes.

Blockchain technology, while often associated solely with cryptocurrencies, has capabilities far beyond the world of finance. Its transparent and secure nature promises to reform industries like supply chain management, healthcare and even elections, reducing fraud and increasing efficiency.

In the realm of communication, 5G technology is set to revolutionize not only how we connect with each other but also how machines interconnect. Its ultra-fast, stable connection and low latency promise to drive the Internet of Things (IoT) to new heights, fostering an era of smart cities and autonomous vehicles.

Virtual and Augmented Reality (VR/AR) technologies have moved beyond the gaming industry to more practical applications. Industries such as real estate, tourism, and education are starting to realize the immense potential of these technologies for enhancing customer experience and learning outcomes.

Quantum computing, though still in its infancy, holds extraordinary promise with its potential to solve complex computational problems at unprecedented speeds. This technology could bring profound impacts to sectors such as pharmacology, weather forecasting, and cryptography.

These breakthroughs represent the astounding future that lies ahead, but they also hint at new challenges to be navigated. As we move forward, questions surrounding ethical implications, data privacy, and security need to be addressed. However, whats undeniable is the critical role technology will play in shaping our collective future. This evolution inspires awe and eager anticipation of what is yet to come.

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Absolutely, here's an article on the impact of upcoming technology - Medium

Elon Musk, the billionaire entrepreneur behind Tesla, SpaceX, and X (Twitter), has launched a new artificial intelligence company called xAI. The companys mission is to understand the true nature of the universe, according to its website. But what does that mean, and why is Musk interested in AI?

AI is the field of computer science that aims to create machines that can perform tasks that normally require human intelligence, such as recognizing images, playing games, or conversing. AI has made remarkable progress in recent years, thanks to advances in hardware, data, and algorithms. Some examples of AI systems are ChatGPT, which can generate realistic text conversations, and AlphaGo, which can beat human champions in the complex board game Go.

Musk has been fascinated by AI for a long time and has also expressed concerns about its potential risks. He co-founded OpenAI in 2015, a research organization that aims to create friendly AI that can benefit humanity without harming it. However, he left OpenAI in 2018 after a disagreement with its leadership over its direction and funding. He has also warned that AI could pose an existential threat to human civilization if it becomes more intelligent than us and decides to eliminate us.

That is why Musk created xAI, which stands for eXplainable Artificial Intelligence. The companys goal is to develop AI systems that can explain how they work and what they are doing, as well as understand the underlying laws of physics and reality. By doing so, Musk hopes to make AI more transparent, trustworthy, and aligned with human values. He also hopes to learn more about the mysteries of the cosmos and our place in it.

xAI has assembled a team of 12 experts from various fields of AI, including former employees of Google, Microsoft, Tesla, OpenAI, and DeepMind. The company plans to work closely with Musks other ventures, such as X (Twitter) and SpaceX, as well as other partners who share its vision.

xAI reflects Musks passion for innovation and exploration, as well as a caution for safety and ethics. Whether xAI will succeed in its mission or not remains to be seen, but one thing is certain: it will not be boring.

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AI: Elon Musk and xAI | Formtek Blog - Formtek Blog

In the giant realm of technological progress, one phenomenon has garnered unparalleled attention and sparked discussions that reverberate across the globethe upward thrust of Artificial Intelligence (AI).

From the speculative landscapes of technological know-how fiction to the tangible realities of today, AI has transcended the boundaries of imagination, leaving an indelible mark on how we live, paint, and envision the future.

Lets embark on an adventure through the riveting international of AI, tracing its origins, exploring its present-day competencies, and thinking of the boundless ability it holds for our ever-evolving future.

The roots of AI delve deep into the annals of human creativeness and clinical curiosity. Early thinkers contemplated the idea of machines mirroring human intelligence, laying the theoretical foundations for what would come to be an innovative field.

Pioneers like Alan Turing contributed seminal ideas, setting the level for the eventual emergence of sensible AI.

The pivotal Dartmouth Conference in 1956 marked the start of Artificial Intelligence as a great shape maker, bringing together exquisite minds to speak about the possibility of making machines that could simulate human idea strategies.

However, early AI packages confronted considerable obstacles, suffering from the complexity of international situations.

The turning point for AI was device learning, a paradigm that empowers structures to analyze from statistics and enhance over time.

This shift has played a critical role in the current surge of AI programs. Milestones in system learning, including improving practical algorithms and extended computing abilities, have propelled AI to new heights.

Within the broader scope of the device, getting to know deep knowledge sticks out as a transformative pressure.

Fueled by neural networks that mimic the human minds structure, deep learning has enabled AI structures to resolve complicated styles and make complex selections.

Notable achievements, which include AlphaGos triumph over human champions, underscore the outstanding skills of deep getting to know.

In the area of healthcare, AI is proving to be a sport-changer. Diagnostic equipment powered by AI can analyze giant datasets to become aware of patterns indicative of diseases, leading to extra accurate and well-timed diagnoses.

Moreover, AI is riding improvements in personalized medication, tailoring remedies to male or female patients based totally on their genetic makeup.

AIs effect extends deeply into the economic quarter. Algorithms electricity algorithmic buying and selling, optimizing investment strategies, and coping with dangers with remarkable precision.

Additionally, AI-pushed packages excel in fraud detection, ensuring the safety of financial transactions and improving customer service stories.

The educational landscape is likewise a present process of change through AI. Personalized getting-to-know studies, facilitated utilizing adaptive algorithms, cater to the man or woman wishes of college students.

AI-driven academic tools provide interactive and tasty content material, revolutionizing traditional teaching strategies.

As AI is based closely on facts, privacy concerns come to the vanguard. The misuse of personal facts and the capability for surveillance boost moral questions.

Striking stability between innovation and privacy protection is essential to fostering consideration in AI technologies.

Looking in advance, the trajectory of AI factors in the direction of groundbreaking improvements. Quantum computing, with its remarkable electricity processing, can revolutionize AI talents.

The integration of AI with other rising technologies, such as augmented truth and the Internet of Things, guarantees the creation of synergies that amplify the impact of AI across numerous domain names.

As AI continues to adapt, ethical issues become increasingly more paramount. Responsible AI research and improvement are vital to ensure that AI technology benefits humanity.

Global collaborations and the establishment of moral requirements are essential steps in navigating the moral complexities of AI.

The upward push of Artificial Intelligence stands as an affidavit to human innovation and the relentless pursuit of information.

AI has grown critical to our contemporary life, from its theoretical origins to its cutting-edge applications throughout numerous industries.

As we confront the worrying conditions and moral issues accompanying this technological ascent, we must method the upward push of machines with a human-centric attitude.

In doing so, we will shape a future wherein AI augments the human revel, fostering sizeable and sustainable progress.

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Rise of the Machines Exploring the Fascinating Landscape of ... - TechiExpert.com

In the 1970s, as researchers started to grasp the intricacies of genetics, they were inevitably faced with the ethical implications of intentionally altering genes in living organisms. While no technology existed at that time to make such modifications, it was clear that its emergence was just around the corner. In 1975, a landmark conference was held in Asilomar, California, bringing together not just scientists but also about 140 professionals ranging from legal experts to writers and journalists. The goal was to address the potential risks associated with gene manipulation. The conference led to the creation of a set of guiding principles that continue to have a lasting impact today. Asilomar serves as a singular example of effective self-regulation, proactive risk mitigation, and open communication with the public.

Today, as we stand on the cusp of a new, AI-driven, era, theres again a palpable sense of anticipation across the globe, while new risks and opportunities spread out before us. AI has swiftly transitioned from being a technological novelty to a pervasive force, reshaping our daily lives and industries, ranging from pioneering projects like OpenAI to autonomous transport. he allure of generative AI applications has dwarfed past technological frenzies. While innovations like the internet, steam engine, and printing press have previously ushered in transformative epochs, AI holds the promise of instigating the most monumental shift in human history.

However, as this wave of innovation surges forward, the need for a comprehensive regulatory framework becomes increasingly urgent. An important goal, agreed by several stakeholders, should be to ensure the ethical, secure, and equitable use of AI for all. The conversation is not a hypothetical debate about the distant future; its about what must be done today to secure a prosperous future for humanity and the planet.

Numerous stakeholdersgovernments, international organisations, NGOs, and tech giants, are scrambling to address the myriad challenges posed by AI. Whether driven by genuine concern or merely to cultivate a contemporary image, different initiatives are underway. The European Commission is pioneering efforts to craft the first-ever legal framework for AI[1]. The proposed legislation establishes different rules for different risk levels and has the potential to address AI risks for the society. Yet, it is uncertain whether this European effort can address all current and especially future challenges. Two glaring gaps persist in the European legislative effort but also in numerous parallel national or international initiatives.

First, the vast majority of the current efforts are focused on the present and the impacts of narrow AI, that is the current version of AI tools capable of performing specific tasks (like ChatGPT, AlphaFold or AlphaGo). Yet, this preoccupation with narrow AI obscures the monumental, potentially catastrophic challenges presented by Artificial General Intelligence (AGI). AGI represents a form of AI with the capacity to comprehend, learn, and apply knowledge across a wide range of tasks and domains[2]. An AGI system connected to the internet and myriad sensors and smart devices could solve complex problems, seek information by any means (even directly interacting with humans), make logical deductions, and even rewrite its own code. AGI does not exist today, yet according to estimations by experts[3] could be available between 2035-2040, a timeline that coincides with the typical time needed to solidify a global AGI treaty and governance system. This synchronicity underscores the pressing need to pivot our focus, infusing foresight methodologies to discern and tackle imminent challenges and prepare for unknown ones.

The second challenge for the ongoing legislative efforts is the fragmentation. AI systems, much like living organisms, transcend political borders. Attempting to regulate AI through national or regional efforts entails a strong potential for failure, given the likely proliferation capabilities of AI. Major corporations and emerging AI startups outside the EUs control will persist in creating new technologies, making it nearly impossible to prevent European residents from accessing these advancements. In this light, several stakeholders[4] suggest that any policy and regulatory framework for AI must be established on a global scale. Additionally, Europes pursuit of continent-wide regulation poses challenges to remaining competitive in the global AI arena, if the sector enjoys a more relaxed regulatory framework in other parts of the world. Furthermore, Article 6 of the proposed EU Artificial Intelligence Act introduces provisions for high-risk AI systems, requiring developers and deployers themselves to ensure safety and transparency. However, the provisions self-assessment nature raises concerns about its effectiveness.

What must be done

In this rapidly changing and complex global landscape, is there any political space for the EU to take action? The pan-European study OurFutures[5] reveals that the vast majority of participants express deep concern about the future, with technology-related issues ranking high on their list, alongside social justice, nature, well-being, education, and community. Moreover, despite the emerging signs of mistrust towards governments globally, citizens in the EU maintain confidence in government leaders as catalysts for positive change (picture 1), while they also prioritize human condition and environment over economic prosperity.

Picture 1: Who are the changemakers and what matters more (OurFutures)

The clock is ticking, but governments still have the opportunity to address societal concerns by taking bold steps. In the case of AI, the EU should assume a leadership role in global initiatives and embrace longtermism as a fundamental value, ensuring a sustainable future for current and future generations:

EU as a global sounding board. While the European Commissions legislative initiative on A.I. signifies a leap in the right direction, structured productive collaboration with key international partners like USA, China, UNESCO and OECD is essential, with the aim to set-up a global AI regulatory framework. The success of the Asilomar conference was rooted in its ability to create a voluntary set of globally respected rules. Violators faced condemnation from the global community, exemplified by the case of He Jiankui[6], who created the worlds first genetically edited babies and was subsequently sentenced to prison. Drawing from its tradition of negotiating regulations with many diverse stakeholders, the EU should champion a global initiative under the UN to forge a consensus on AI regulation, and adapt to the diversity of approaches shown by other AI actors.

A technology monitoring system. A global technology observatory has been already suggested by the Millennium Project[7], the Carnegie Council for Ethics in International Affairs[8] and other experts. This organization should be empowered to supervise AI research, evaluate high-risk AI systems, and grant ISO-like certifications to AI systems that comply with standards. It should track technological progress and employ foresight methods to anticipate future challenges, particularly as AGI looms on the horizon. Such an entity, perhaps aptly named the International Science and Technology Organization (ISTO), building on the work done by ISO/IEC and the IEEE on ad hoc standards, could eventually extend its purview beyond AI, encapsulating fields like synthetic biology and cognitive science. Avoiding the usual challengesdissent over nuances, apprehensions of national sovereignty, and the intricate dance of geopolitics, could be done through the emergence of such an organism from the mentioned already extant standardization organizations. However, the EU, with its rich legacy, is perfectly poised to champion this cause, in close collaboration with the UN to expedite its realization.

Embrace Longtermism. Longtermism, the ethical view that prioritizes positively influencing the long-term future, is a moral imperative in an era of exponential technological advancements and complex challenges like the climate crisis. Embracing longtermism means designing policies that address risks as we transition from sub-human AI to greater-than-human AI. For the European Commission, initiatives to address AI challenges should not be viewed as mere regulation but as a unique opportunity to etch its commitment to a secure, ethical AI future into history. A longtermism perspective in AI matches with the idea of AI Alignment put forth by numerous scholars[9], which addresses diverse concerns related to AI safety, aiming to ensure that AI remains aligned with our objectives and avoids unintended consequences of going astray.

As the world races against the clock to regulate AI, the EU has the potential to be a trailblazer. EUs initiatives to address AI challenges should not be considered merely as a regulatory endeavorits an unparalleled opportunity. Embracing longtermism and spearheading the establishment of an ISTO could be EUs crowning achievement. Its time for the EU to step up, engage in proactive diplomacy, and pave the way for a sustainable AI future that respects the values and concerns of people today and tomorrow.

[1] https://digital-strategy.ec.europa.eu/en/policies/regulatory-framework-ai

[2] https://www.gartner.com/en/information-technology/glossary/artificial-general-intelligence-agi

[3] Macey-Dare, Rupert, How Soon is Now? Predicting the Expected Arrival Date of AGI- Artificial General Intelligence (June 30, 2023). Available at SSRN:https://ssrn.com/abstract=4496418

[4] For example https://www.forbes.com/sites/hecparis/2022/09/09/regulating-artificial-intelligenceis-global-consensus-possible/?sh=a505f237035c

[5] https://knowledge4policy.ec.europa.eu/projects-activities/ourfutures-images-future-europe_en

[6] https://www.bbc.com/news/world-asia-china-50944461

[7] https://www.millennium-project.org/projects/workshops-on-future-of-worktechnology-2050-scenarios/

[8]Global AI Observatory (GAIO) : https://www.carnegiecouncil.org/media/article/a-framework-for-the-international-governance-of-ai

[9] For example: http://lcfi.ac.uk/projects/completed-projects/value-alignment-problem/

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What can the current EU AI approach do to overcome the challenges ... - Modern Diplomacy