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AI Mount Fuji's Call:

The Snail's Unwavering Journey Amidst Shifting Sands


The AI Summit New York, held on December 6-7, 2023, was a notable event in the AI industry, marking its eighth year. This conference was a significant convergence point for industry executives, startup innovators, and commercial leaders. It focused on the future of applied AI across various sectors, including healthcare, finance, government, retail, and aerospace. The event featured a range of panels and discussions, with notable speakers from companies like Microsoft, OpenAI, Google, and AWS. Topics included generative AI in business, government regulation in AI, and corporate implementation of AI technologies. The summit offered a comprehensive platform for exploring practical AI solutions and their real-world applications, emphasizing the translation of technological advancements into business ROI​.

In recent times, a significant AI Summit took place in New York, attracting participants from diverse regions of North America. This event served as a hub for learning, collaboration, forecasting, and knowledge sharing in the rapidly evolving domain of Artificial Intelligence (AI). Over the years, this summit has seen remarkable growth, with attendance and exhibition space expanding substantially since 2018, now featuring three times the number of panel discussions and exhibition space.

The landscape of commercial AI applications is still in its nascent stages, evoking a sense of exploration, analysis, and experimentation. This vibe permeated the conference, whether at exhibitor booths or during one-on-one interactions among attendees. Long-term success in this realm hinges on forging the right partnerships and gaining critical insights.

While some of the knowledge exchanged during the event may be familiar to those closely following the AI sector, there were intriguing insights, particularly at the intersection of AI and media/entertainment, that piqued the interest of investors.

Keep an eye on companies excelling in crafting AI-generated storytelling. According to Rajavi Mishra from Amazon AGI, who addressed the audience, prompts emphasizing context, tone/style, and multi-turn conversations are pivotal in crafting engaging and creative stories using AI. Thus far, AI has demonstrated significant success in generating short-form content. Given the strong appetite, especially among younger consumers, for short-form videos, Mishra suggested that long-form content consumption might decrease. However, it is crucial to consider the human context in which long-form content remains desirable. Therefore, evaluating content quality and uniqueness, irrespective of length, could be a prudent approach.

What remains indisputable, however, is the significance of targeting the right demographic for content. Companies possessing this capability are poised for success. Moreover, we can anticipate the emergence of more potent algorithms for matching content with viewers, potentially challenging today's leading players in the streaming market.

Pay attention to entertainment conglomerates effectively managing their internal data systems. Corporations face a substantial challenge not only in harnessing extensive internal data but also in determining which data to prioritize and how best to analyze it. The prevailing trend involves utilizing AI to organize data and subsequently using data to enhance AI—a seemingly endless cycle that consumes senior management and data executives. Another challenge is establishing seamless systems to train employees in effectively utilizing AI in their daily tasks while complying with ever-evolving legal requirements, addressing bias concerns, and reducing system inaccuracies (referred to as "hallucinations"). Companies adept at navigating these challenges swiftly will gain a competitive edge in the market that will be hard to match.

Sesh Iyer, BCG X North American Chair & Managing Director and Senior Partner at BCG, posits that "GenAI" will usher in a new level of productivity, impacting various facets of work. He predicts significant changes in business models to accommodate AI-driven value propositions. Organizations investing in marketing and content capable of rapid response to consumer needs are poised for substantial benefits. This transformation will not be confined to a few enterprises; it will create significant disparities, with some companies outpacing others by excelling in these areas early on.

Be on the lookout for promising startups. The AI landscape is not the exclusive domain of large corporations. The true test lies in whether startups can navigate their way through established hierarchies swiftly enough to outpace nimble competitors. These startups may not require decades' worth of internal data archives and can swiftly align with consumer desires and interests, generating new offerings. Michael Stewart from M12, Microsoft's Venture Capital Fund, assesses investment opportunities by examining three key factors: the startup's data concept, tooling/infrastructure, and applications. Startups excelling in these areas, particularly in AI application accuracy, will be highly sought after.

Interestingly, Stewart also envisions potential for ChatGPT as an entertainment entity, likely to be integrated into gaming by various startups—a compelling prospect to monitor in the marketplace.

Regardless of the specific offering, Nicolas de Bellefonds, Managing Director & Senior Partner at BCG, emphasizes that being in the middle ground is precarious. Companies without the corporate size to drive large-scale operations or the agility of startups face significant challenges and may struggle to thrive.

Another noteworthy aspect discussed at the event is the importance of diversity, equity, and inclusion (DEI) in AI. Diverse perspectives in AI decision-making are considered crucial for success, particularly as AI enables deeper personalization of media and entertainment content.

Lastly, keep an eye on unique applications involving voice data and AI. Companies offering impeccable transcription capabilities, video editing based on transcription, and AI-driven speech technology are poised to redefine creativity and originality. Over the next year, anticipate the emergence of custom AI models centered around voice, including nearly real-time translation, which will create new business opportunities in the media/entertainment space.

However, while these possibilities are exciting, they also come with challenges such as errors, confusion, and unauthorized use. Many are seeking industry-wide solutions to address these concerns. Companies that can provide these solutions may become highly valuable in this rapidly evolving sector.

In conclusion, the AI market is vast and plays a central role in the contemporary civilization's added value. However, security and global consequences remain shrouded in uncertainty. It's concerning that officials often disregard these critical issues, especially considering the imminent arrival of displaced labor. Addressing a range of issues, from essential infrastructure to security, should be a top priority. Unfortunately, this vital matter doesn't seem to garner much interest from certain officials and local authorities who may not fully grasp the impending challenges akin to a tsunami wave.

Above is the list of all the Summit participants, but I have taken the courage to name a few below:


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  1. Large Graphical Models (LGMs): LGMs represent a groundbreaking approach in AI, offering efficient, probabilistic data representation. This is particularly beneficial for domain-agnostic learning, which is crucial in diverse applications such as forecasting and scenario planning. The versatility of LGMs lies in their ability to process and analyze vast amounts of data across various fields, making them indispensable tools for organizations dealing with complex, multi-dimensional datasets.
  2. eXpert-in-the-Loop System: This system is an innovative fusion of AI with human expertise. It allows experts to directly infuse AI models with their nuanced knowledge and intuition. This collaboration between human intelligence and AI algorithms enhances the accuracy and relevance of the AI's outputs. It is particularly beneficial in sectors like banking and retail, where decision-making often requires a blend of data-driven insights and human judgment. This system not only improves the precision of AI systems but also ensures that they remain adaptable and aligned with the evolving complexities of the industry.

Together, these innovations position as a leader in the AI domain, offering solutions that are not just technologically advanced but also practical and adaptable to real-world scenarios. Their approach emphasizes a new paradigm in AI-human interaction, essential for industries that rely on both data accuracy and human expertise.



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Cerbrec's Graphbook emerges as a cutting-edge tool in the AI development landscape, addressing key pain points that AI developers often face. Its specialized focus on three critical areas showcases a deep understanding of the needs in the narrow but crucial business-to-business (B2B) sector.

  1. Streamlined Compute Environment Management: Graphbook addresses the often-overlooked but essential aspect of compute environment management. By streamlining this process, it makes AI development more convenient, reducing the friction often encountered in setting up and maintaining the necessary computational infrastructure.
  2. Transparent AI Modelling: The platform emphasizes transparency in AI modeling, which is vital in the field. This clarity and openness could be the deciding factor in the success or failure of an analysis, affecting critical decisions based on AI insights.
  3. Effortless Model Debugging: Acknowledging the challenges in AI model debugging, Graphbook offers solutions that simplify this process. This feature is particularly valuable, given the complexity and often time-consuming nature of debugging AI models.

About Graphbook

Graphbook stands out as a novel visual Integrated Development Environment (IDE) for AI and deep learning model development. Its unique selling point is the ability to build and run models directly on a visualization platform. This approach allows for direct customization of transformers, training, and serving them via a URL. Currently in beta mode, Graphbook is continuously evolving, adding more models and product features.

Future Plans and Community Engagement

Cerbrec plans to progressively open-source Graphbook, enhancing accessibility to its APIs. This initiative will likely broaden the platform's user base and foster a collaborative environment. Interaction with backend services is streamlined through a client application available on their website. The company actively engages with its user community through its website documentation, YouTube tutorials, and an open repository for issue tracking and model template sharing.

Impact in the AI Industry

Graphbook, and companies like Cerbrec, play a pivotal role in the AI sector for several reasons:

  • Innovation in AI Technologies: By developing new algorithms and techniques, they are pushing the boundaries of machine learning, data analysis, and automation.
  • Applications Across Industries: The versatility of AI models developed through platforms like Graphbook extends to healthcare, finance, automotive, and more, aiding in predictive analyses.

Recall that we still utilize Fortran code dating back to the 1970s, and consider the enduring use of COBOL, a programming language initially developed in 1959 and still prevalent in the banking sector today. This historical perspective underlines the critical importance of structured debugging in model technologies. Maintaining and updating these longstanding systems is essential, as they continue to play a pivotal role in various industries.


broken image has distinguished itself in the artificial intelligence (AI) landscape, primarily through its groundbreaking work in "precision AI." This innovative approach is a testament to the visionary leadership of Srinivas Kilambi, Ph.D., CFA, whose diverse career in academics, research, and the corporate sector has been integral to the development of's core technology.

Core Development by Dr. Srinivas Kilambi

Dr. Kilambi, an inspirational entrepreneur, alongside his team, dedicated years to crafting a highly complex and robust deep-tech AI-ML algorithm solution. This technology is at the heart of's ability to deliver exceptional precision across various domains, such as clinical analysis, stock market forecasting, and healthcare.

1. Precision AI in Clinical Analysis

In clinical settings,'s precision AI technology marks a significant advancement over traditional AI models, claiming nearly 60% more precision. This high degree of accuracy is crucial in interpreting medical data, directly impacting patient outcomes and treatment plans.

2. Impact on Stock Market Analysis

The application of precision AI extends to stock market analysis, where reports a nearly 30% improvement in precision. This capability is vital for financial analysts and investors, enabling more accurate market predictions and risk assessments.

3. Advancements in Healthcare also boasts about an 11% improvement in precision in the broader healthcare sector. This progress is significant in developing more precise diagnostic tools, personalized treatment strategies, and efficient healthcare management systems.

Overall,, under Dr. Kilambi's guidance, has made significant strides in AI and machine learning. His expertise in machine learning to support biotechnology, nanotechnology, and digital user experience has been pivotal in establishing the company's unique strengths in precision AI. The advanced technology developed by represents a substantial leap in accuracy and efficiency, positioning the company as a key player in the evolving AI and machine learning landscape. This innovation underscores the importance of precision in high-stakes domains such as clinical analysis, stock market forecasting, and healthcare, setting a new benchmark in AI applications.


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In the rapidly evolving digital landscape, the ability to process and manage large volumes of data efficiently is crucial for large institutions. ZL Tech has emerged as a leading solution provider in this domain, offering a unified platform that encompasses various aspects of data management and processing.

Real-Time Data Processing

ZL Tech specializes in enabling real-time data processing, a critical need for decision-making and maintaining operational efficiency. This capability allows organizations to stay competitive by providing immediate insights and responses to rapidly changing data landscapes.

Unified Platform

Their unified platform is designed to integrate different data management tools into a single system. This not only streamlines workflows but also significantly reduces complexity, enhancing overall efficiency and effectiveness in managing data.

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Unstructured Data Management

With the increase in unstructured data, such as emails, social media posts, and multimedia content, ZL Tech's solutions utilize AI and machine learning to manage this data effectively. This involves categorizing, analyzing, and extracting valuable insights from vast and varied data sources.

Integration with Microsoft 365

ZL Tech also offers seamless integration with Microsoft 365, enhancing collaborative work environments. This integration includes a suite of tools for communication, scheduling, document management, and more, creating a comprehensive ecosystem for business operations.

Handling Unsorted Messages

Efficient management of unsorted messages is another critical feature of ZL Tech's platform, crucial for customer communication, support tickets, and internal coordination. This ensures that important communications are not lost or overlooked.


  • SEARCH: The platform provides robust search capabilities to identify and cull data for eDiscovery and privacy regulations.
  • ENFORCE: It enforces retention and compliance policies, allowing for the defensible deletion of documents in line with privacy and records management.
  • CAPTURE: The platform captures insights into workforce and business operations through on-the-fly analytics.
  • GOVERN: ZL Tech enables comprehensive governance of enterprise data with both in-place and selective archiving strategies.

In summary, ZL Tech's unified approach to data management caters to the complex needs of modern organizations. By addressing key aspects of data management, such as real-time processing, unstructured data management, and integration with essential business tools, ZL Tech positions itself as an indispensable partner in the realm of enterprise data management.


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What is Drone Racing? The essence of drone racing lies in navigating complex courses rapidly and precisely, often surpassing other competitors in speed and maneuverability. Competitions occur in diverse venues, ranging from large stadiums to virtual environments, allowing pilots to compete globally. Pilots also engage in virtual races using platforms like the DRL SIM, a realistic drone racing simulator that emulates the physical racing experience.

Drone Racing League (DRL)

The Drone Racing League (DRL) stands as the premier league for professional drone racing. It attracts the world's most talented drone pilots, who fly custom-built racing drones at speeds of up to 90 MPH through intricate courses. The DRL ingeniously combines the digital and physical worlds, featuring innovative drone technology, immersive content, and visually stunning races broadcasted globally on platforms such as NBC, Twitter, TikTok, YouTube, Fox Sports, Sky Sports, ProSieben, and Weibo.

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While drone racing is closely associated with gaming, leisure, and entertainment, it also parallels the evolving landscape of modern warfare, particularly highlighted by the recent conflicts like the Russian aggression against Ukraine. The rise of drone technology, enhanced by AI, has become increasingly relevant in modern warfare, offering new tactics and strategies in radio electronic warfare.

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Drones, once seen primarily as recreational devices or racing tools, have now taken a significant role on the battlefield. They provide real-time intelligence, surveillance, and, in some cases, offensive capabilities without risking human life. The skills developed in drone racing, such as precision control and rapid navigation, find a parallel in military applications where similar competencies are vital.



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OpenText, renowned for its leadership in information management solutions, has seamlessly blended its expertise in artificial intelligence (AI) with robust information management to create a dynamic business environment. Their approach is not just about integrating technology; it's about reimagining how businesses operate in a digital world.

Scaling Operations for a Digital Future

OpenText's information management solutions are designed to scale business operations for a digital future. They enable organizations to work smarter by organizing, integrating, and protecting data across business processes. This comprehensive approach helps businesses securely manage information flows, thereby gaining a significant information advantage.

Benefits of Information Management

OpenText’s solutions reduce risks, cut costs, and grow revenue. Their integrated information management platform is instrumental in managing information end-to-end, streamlining operating models and enhancing customer journeys.

Connecting Everything That Matters

By integrating systems, people, content, and things, OpenText delivers enriched information in context, exactly where it’s needed. This integration is key to simplifying governance and compliance, embedding these crucial aspects into business processes without impacting productivity.

Accelerating Business in the Cloud

OpenText offers diverse cloud solutions, including public cloud, private cloud, on-premises, or developer API services. These options cater to accelerating digital transformation, meeting the highest industry standards.

OpenText AI: A Strategic Edge

  1. Custom AI Solutions: OpenText excels in offering custom AI solutions, tailoring them to unique business needs and objectives.
  2. Advanced Data Analysis: Their AI Cloud platform specializes in analyzing massive data, providing insights for improved decision-making.
  3. Intelligent Recommendations: Through OpenText Magellan, they drive sales by offering AI-driven personalized product recommendations.
  4. AIOps for IT Operations: The company enhances IT efficiency by applying AI and machine learning in IT operations.
  5. Reliability and Expertise: OpenText's reputation and expertise in AI and analytics solidify its position as a reliable solution provider.

OpenText's integration of AI and information management solutions represents a powerful combination of innovation, customization, and practical application. Their approach caters to current business needs and anticipates future trends, positioning them as a key player in AI and information management, ready to tackle the challenges of the digital era.


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Fetch AI, a pioneering force in the realm of artificial intelligence, has introduced an innovative AI Engine that is reshaping the way users and developers interact with AI technologies. This next-generation system is built upon the synergy of agent-based services and the AI Engine ecosystem, offering a sophisticated platform for connecting a wide array of services.

Personalized Capabilities and Large Language Models

At the heart of Fetch AI's AI Engine lies the power of Large Language Models (LLMs), which are instrumental in driving the engine's understanding, coordination, and problem-solving abilities. The system is designed to spawn an internal agent for each user. Once the user's intent is communicated, this agent starts working asynchronously, tailoring its actions to the user's specific needs.

Catalyzing Connections in the AI Ecosystem

The AI Engine ushers users and developers into a unified ecosystem of agent-based services. Once a service is registered, it becomes a part of the AI Engine's expansive landscape, enabling dynamic and efficient interactions between users and various services.

The Engine’s Sophisticated Architecture: Objectives and Tasks

At its core, the AI Engine's operation is driven by two fundamental components: Objectives and Tasks.

  • Objectives: These are the foundational elements of the AI Engine's functionality, encapsulating the general goals of users in natural language. They provide direction and purpose to the engine's actions.
  • Tasks: Tasks represent a dynamic sequence of steps aimed at achieving the defined objectives. These tasks are intricate, involving resource allocation, time management, and other interdependencies, all managed efficiently by the agent-based services.

Deconstructing Tasks: Comprehension, Planning, and Context Building

The essence of the AI Engine is distilled into two critical functions:

  1. Comprehension and Planning: This process involves taking the user's objectives and transforming them into a series of sub-tasks, each a step towards the final goal. This orchestration can be autonomous or involve user input for task validation.
  2. Context Building: The AI Engine continuously collects and transforms information, enriching its understanding and refining the knowledge landscape throughout the user’s interaction with the engine.



Fetch AI's AI Engine represents a significant leap in the field of artificial intelligence. By harnessing the synergy of agent-based services and advanced AI technologies, the platform offers personalized, efficient, and intuitive interactions between users and AI services. This innovative approach positions Fetch AI as a leader in the AI industry, paving the way for more intelligent and interconnected AI solutions.


I simply love this company,, which has emerged as a remarkable force in the realm of AI, offering solutions that transcend traditional data analysis methods. Their platform provides insightful connections through subtle covariations, patterns, and hints, heralding a new era in data intelligence and decision-making. This evolution is not just for IT experts and mathematicians but for all of humanity, to address everyday challenges and to inspire grander thinking.

Generative AI: The New Frontier in Data Analysis

Generative AI has revolutionized how we interact with data, creating content from simple prompts, including images, texts, audio, video, and various data forms. Its potential to transform data analysis across numerous fields is immense. However, its widespread adoption faces several hurdles:


Resource Scarcity

The limited availability of data science experts hampers AI adoption. Organizations struggle to find talent that can translate vast data into actionable insights. The data science pool is not only small, but those in the field are often overloaded with tasks, leaving little room for AI-focused projects.


Trust Issues

Beyond the fears of AI's potential misuse, there is a general lack of confidence in AI-generated results. This distrust is fueled by a knowledge gap about AI solutions and their implications. Issues like AI "hallucinations" or misinformation arise from incomplete queries or inaccurate datasets, exacerbating trust issues.


Usability Challenges

Many AI tools are not user-friendly, requiring specialized data science knowledge, thus limiting their accessibility to a broader user base.

Intelligent Data Exploration by Virtualitics

Virtualitics tackles these challenges by offering a platform for Intelligent Exploration, Explainable AI (XAI), and Large Language Models (LLMs). This approach simplifies AI for the average user through:

  • Embedded AI routines for generating multidimensional visualizations.
  • Natural language delivery of key insights, supported by AI-generated visualizations.
  • LLM suggestions for further analysis based on user prompts, ranging from specific to open-ended.

Enhancing User Experience with XAI and LLMs

XAI aims to balance model interpretability with accuracy, offering context-aware explanations suitable for non-expert audiences. LLMs overcome the limitations of traditional NLP systems by presenting results in narrative forms, making them more accessible and understandable.

The Vision of Ciro Donalek and Virtualitics

Ciro Donalek, a leading AI and data visualization expert, plays a pivotal role in Virtualitics' journey. His expertise in machine learning and AI, combined with a passion for teaching and ethical AI, drives the platform's vision. Virtualitics is not just about data analysis; it's about making AI a powerful, accessible tool for all, transforming how we interact with data and make decisions.

Virtualitics exemplifies how AI can be democratized for broader societal benefit. By enhancing resources, building trust, and improving usability, Virtualitics paves the way for a future where AI is not a specialized tool but a universal ally in understanding and navigating our increasingly complex world.


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RAG, Rambo among the AI platforms. In an era where real-time data retrieval and tailored responses are crucial for businesses, the current chat GPT models often fall short in meeting these specific needs. This gap is especially evident in industries like real estate, grocery, and hedge funds, where data is dynamic and decision-making is time-sensitive. Enter the Shakudo RAG Stack, a game-changer in the world of AI and data management.

The Shakudo RAG Stack: A Tailored Approach to LLM

Production-Ready System

The Shakudo RAG (Retrieval-Augmented Generation) Stack stands out as the fastest and most cost-effective way to implement a RAG-based Large Language Model (LLM) system tailored to a business's unique requirements. This system allows businesses to select their preferred data source, vector database, and LLM, ensuring a customized and efficient solution.

Real-Time Data Handling

One of the key strengths of the Shakudo RAG Stack is its ability to handle real-time data retrieval and responses. This capability is crucial in sectors where data changes rapidly and decisions need to be made quickly based on the latest information.

Accelerating the Impact of Emerging Technologies

Shakudo’s team comprises experts in data and AI, dedicated to creating an operating system for the modern data stack. Their focus is not just on the technology itself but also on fostering an inclusive and diverse culture, bringing together unique perspectives and skills to innovate in the field of AI and data analytics.

Industries Benefiting from Shakudo RAG Stack

The flexibility and adaptability of the Shakudo RAG Stack make it an ideal solution for various industries:

  • Real Estate: For market analysis, property valuations, and trend predictions.
  • Grocers: In managing supply chains, customer behavior analysis, and inventory optimization.
  • Hedge Funds: For market trend analysis, risk assessment, and investment strategy optimization.

The Shakudo RAG Stack represents a significant step forward in making AI more accessible and relevant to businesses needing real-time data analysis and decision-making tools. Its ability to be tailored to specific industry needs makes it a powerful ally for businesses looking to leverage the full potential of AI in their operations. As we move forward, Shakudo continues to shape the future of data and AI for commercial use, marking a new era in intelligent business solutions.


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Pangeanic's approach centers around optimizing Retrieval-Augmented Generation (RAG) systems and customizing LLMs to ensure data privacy while maintaining accessibility across organizations. This approach significantly boosts productivity in knowledge extraction, information retrieval, content generation, machine translation, anonymization, and more.

Featured Language Solutions:

  1. Natural Language Processing:
  • Training datasets for creating AI models and LLMs.
  • Specializing LLMs for practical applications at an enterprise level.
  • Scaling up content processing in monolingual and multilingual formats.
  1. Machine Translation:
  • Specialized models with user-specific terminology and style.
  • Integration with main translation tools and private SaaS or cloud ecosystems.
  • Ranked 1st in Spanish and 4th worldwide, offering a fast and private translation environment.
  1. Professional Translation Services:
  • Tech-enabled services recognized by Gartner.
  • Combining technology with human expertise for high-quality translations.
  1. ECO Platform and PECAT:
  • Proprietary platforms ensuring complete privacy and global language expertise.
  • Services include data anonymization/masking, annotation, and system evaluation.
  1. Anonymization:
  • The first multilingual anonymization software in the world.
  • Protecting data and privacy for various high-profile European entities.
  1. Text and Data Classification:
  • Utilizing LLMs and semantic tools for automatic classification.
  • Human-in-the-loop review with PECAT tool for additional accuracy.

Pangeanic: Making AI Human-Centric

With the slogan "Pangea united all continents. We believe AI can make us better humans," Pangeanic epitomizes the fusion of technology with human intelligence. Their commitment to ethical AI and data privacy puts them at the forefront of transforming the translation industry and other data-intensive sectors. By making AI accessible and practical, Pangeanic is not only solving mundane issues but also empowering humanity to think bigger and work smarter.


In the rapidly evolving field of Artificial Intelligence (AI), breakthroughs are happening at an unprecedented pace. One such groundbreaking development is TemporAI, an AI company making waves in the most renowned AI venues globally despite not yet having a website. TemporAI stands out as a testament to how quickly innovations in AI are reshaping industries.


TemporAI is a machine learning-centric time-series library tailored for the medical field. Its focus areas include time-to-event (survival) analysis using time-series data, exploring treatment effects over time (causal inference), and making time-series predictions. This library aims to address specific medical and healthcare needs, providing critical data preprocessing methods like missing value imputation for both static and temporal covariates. Additionally, TemporAI offers AutoML tools for hyperparameter tuning and pipeline selection, enhancing its usability.

Unique Features

TemporAI's uniqueness lies in its:

  • Medicine-First Approach: It's specifically designed for medical and healthcare applications, such as survival analysis, temporal treatment effects, and imputation methods.
  • Fast Prototyping: The plugin design allows quick integration of new methods by users, facilitating rapid development and application.
  • Research to Practice Transition: Incorporating novel models from the research community into practical applications.
  • Healthcare Ecosystem Vision: Planned tools include interactive demonstration apps, new medical problem settings, and interpretability tools.

Key Concepts and Installation

TemporAI can be installed via pip or directly from the source. It is designed to be user-friendly, allowing easy access and experimentation. The library includes various plugins for different tasks, from survival analysis to treatment effects modeling.

TemporAI Ecosystem

The ecosystem includes:

  • temporai-clinic: A web app for interacting with TemporAI models and visualizing data and predictions.
  • temporai-mivdp: An adaptation of the MIMIC-IV-Data-Pipeline for TemporAI, enhancing its data handling capabilities.

Development and Contribution

TemporAI encourages contributions, offering a comprehensive guide for developers and testers to contribute to its growth. It invites collaboration and suggestions, aiming to create a robust, community-driven tool.

Citing TemporAI

For academic use, TemporAI provides a citation format, acknowledging its contribution to the field of machine learning in medicine.

TemporAI exemplifies the rapid pace of AI development, especially in specialized fields like medicine. Its focus on medical time-series data and its innovative approach make it a promising tool for healthcare professionals and researchers, highlighting the transformative power of AI in medicine.


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Arthur, a leader in AI deployment solutions, has made significant strides in the realm of AI and ML operations. With a heritage of over 50+ years in industry and academic expertise, Arthur has adopted a research-led approach to product development. The result is the launch of Arthur Chat, a groundbreaking AI chat platform designed for businesses. This solution seamlessly integrates AI chat apps with proprietary data, significantly simplifying the deployment process from ideation to fully operational chat platforms.

Arthur Chat stands out for its adaptability to integrate with any language model, bolstered by Arthur Shield's proprietary safety mechanisms. These mechanisms provide real-time protection against sensitive data leakage, prompt injections, and inappropriate content generation. A unique feature of Arthur Chat is its built-in hallucination detection, ensuring unparalleled reliability in AI chat interactions.

Arthur's innovative approach is already being utilized by leading financial institutions and fintechs like ECI. These organizations are leveraging Arthur Chat's capabilities to automate information discovery and deliver robust, customized AI solutions. The platform's flexibility allows enterprises to switch between language models with ease, maximizing the latest AI technologies' potential while safeguarding their internal, proprietary data.

Arthur Chat is designed for diverse applications across sectors:

  • Finance: Offers specific market insights and data leveraging proprietary information.
  • Retail: Customizes chatbots for specific product information.
  • Customer Support: Delivers dynamic, precise responses based on unique enterprise data.

Key Features of Arthur Chat:

  • Arthur Shield: Ensures comprehensive real-time protection and monitoring against various AI risks.
  • API Integrations: Facilitates smooth transitions between different language model providers.
  • Customizable Data Integration: Employs proprietary enterprise data for tailored chat responses.

Adam Wenchel, CEO of Arthur, emphasizes the platform's ability to leverage unique data for building competitive advantages and accelerating productivity. Arthur Chat is a testament to Arthur's commitment to delivering AI-driven solutions that are accurate, data-secure, and value-aligned.

In addition to Arthur Chat, the company offers Arthur Bench, an open-source evaluation product that aids businesses in selecting the most suitable LLM for their needs. It emphasizes model selection, validation, budget, and privacy optimizations. Furthermore, Arthur Shield stands as the world's first firewall for LLMs, addressing the risks associated with deploying and utilizing LLMs.

With a recent raise of $42M in Series B funding, Arthur is set to scale up to meet the burgeoning demand for essential AI infrastructure. The investment underscores Arthur's leading position in machine learning observability and its pivotal role in ensuring AI's transformative potential is realized with accuracy, transparency, and fairness.

Arthur continues to lead in AI Performance solutions for computer vision and NLP, offering unmatched enterprise scalability, bias detection and mitigation, and a research-led approach to development. The platform has enabled top financial services firms to save millions in operating expenses and increase model-driven revenues significantly.

About Arthur:

Arthur is the AI performance company focused on monitoring, measuring, and improving machine learning models to deliver superior results. Their platform works with enterprise teams to accelerate model operations and optimize for accuracy, explainability, and fairness. Arthur's unique research-led approach fosters exclusive capabilities in enterprise scalability, computer vision, NLP, and bias mitigation.


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Hired is a pioneering company that aligns with contemporary AI trends in the recruitment industry, significantly innovating the hiring process. Their approach revolutionizes the traditional method of recruitment by flipping the script: instead of candidates inundating companies with CVs, Hired enables
employers to actively seek out potential hires. This method not only streamlines the hiring process but also ensures that candidates' profiles are adequately reviewed and considered.

Key Innovations of Hired:

1. Active Employer Engagement: Hired facilitates aplatform where employers reach out to potential candidates, making the hiring process more efficient and targeted​​.

2. Remote Work Emphasis: Reflecting the globaltrend towards remote work, Hired focuses on candidates who prefer or require remote working arrangements, acknowledging the future trajectory of the workforce​​.

3. Global Talent Pool: By not limiting theirscope to a single country, Hired assembles multinational teams, leveraging global talent to meet diverse organizational needs​​.

4. AI and Tech Focus: The company places asignificant emphasis on AI, utilizing its capabilities to streamline the recruitment process, from identifying potential candidates to assessing their fit for specific roles​​.

5. Diverse Industry Concentration: Hired doesn't justfocus on tech roles but also includes sales within the tech industry, ensuring a broad spectrum of opportunities for candidates and employers alike​​.

6. Advanced Candidate Assessment: They employ real-worldskill assessments to gain deeper insights into candidates' capabilities, leading to better job fit and faster hiring decisions​​.

7. Pre-Negotiated Salary Terms: Hired facilitates thenegotiation of salary, bonuses, and compensation packages even before candidates engage in discussions with potential employers, streamlining the hiring process​​.

Hired's model is a reflection of how AI is reshaping therecruitment landscape, offering innovative solutions for more effective and efficient talent acquisition. From AI-driven reference checks to internal mobility and AI-powered talent marketplaces, the recruitment industry is witnessing a significant transformation, enhancing both the recruiter's and candidate's experience​​​​.

The integration of AI in recruitment is not just a fleetingtrend; it's an evolving practice that is becoming increasingly sophisticated, making the hiring process faster, easier, and fairer. The innovations brought
forth by companies like Hired are indicative of a larger shift in the industry, where technology and human expertise combine to create more meaningful and productive employment relationships.


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Neo4j, a pioneer in graph technology, is revolutionizing how organizations manage and interpret complex data. With its versatile applications, Neo4j stands out in several key areas:

  1. Fraud Detection: Neo4j excels in identifying fraudulent activities by analyzing intrinsic connections within data. Its graph database approach enables the detection of sophisticated fraud patterns that traditional databases might miss. This capability is particularly beneficial in sectors like finance and e-commerce where fraud detection is critical.
  2. Real-time Recommendations: Neo4j enhances customer experience through its real-time recommendation systems. By analyzing customer behavior in relation to products and services, Neo4j provides businesses with actionable insights to improve customer engagement and satisfaction.
  3. Bill of Materials Management: For large inventories, such as those managed by the military, Neo4j's bill of materials application is invaluable. It efficiently handles complex data involving expiration dates, validity, and wear and tear, streamlining inventory management processes.
  4. Track and Trace in Logistics: In logistics and supply chain management, Neo4j's track and trace capability offers a robust solution for monitoring goods and analyzing industry trends. This feature is essential for optimizing logistics operations and managing supply chains more effectively.
  5. Network and IT Operations: Neo4j supports sophisticated graph analysis in network and IT operations. This application is crucial for understanding complex network structures and enhancing IT operational efficiency.

Newsweek recognized Neo4j as a Global Top 100 Most Loved Workplace in 2023, a testament to its positive work culture and commitment to fostering collaborative and innovative environments.

Interesting is the Company History, it was founded a while ago:

  • 2000: Neo4j's founders began developing the first prototype to address RDBMS performance issues.
  • 2003: The first 24×7 production deployment of Neo4j.
  • 2007: Neo4j was open-sourced under the GPL, marking a significant milestone.
  • 2010-2022: Neo4j underwent significant growth, including multiple funding rounds, the release of major versions, and expansion into various data science services.
  • Today: Neo4j is used by thousands of organizations, from startups to Fortune 500 companies, for applications including fraud detection, master data management, and risk management.

Neo4j's journey reflects its commitment to innovation and excellence in graph technology, making it a leading choice for organizations looking to leverage the power of graph databases.


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Graphen AI is a pioneering company that harnesses the immense potential of artificial intelligence to create innovative solutions across various industries. Their philosophy revolves around the concept of the human brain as a complex graph, with numerous nodes and edges performing essential functions such as memory, observation, judgment, perception, abstract reasoning, and strategy. In their pursuit of emulating human intelligence, Graphen AI emphasizes the significance of graph technology.

Over two decades, Graphen's team of researchers and developers has been committed to advancing AI technologies, leveraging graph infrastructure's capabilities. Their work spans across multiple fields, including cognitive security, employee productivity enhancement, intelligent machine development, big data management, and enhancing reasoning and understanding.

Graphen AI's approach to AI is industry-specific, offering services, solutions, and products tailored to the needs of the finance, medical, automotive, energy, and security sectors. This strategy is grounded in their 'Full Brain' concept and its derivative brains, which embody deep industry knowledge.

One of their flagship initiatives, Ardi, named after a 4.4 million-year-old human-like anthropoid, aims to replicate all functions of the human brain. Ardi encompasses 11 toolkits - Memory, Perception, Learning, Understanding, Reasoning, Strategy, Expression, Personality, Emotion, Knowledge, and Action. These modules can be orchestrated through a Pipeline, mimicking human cognitive processes.

Graphen AI's industry platforms include:

  1. Alpha: AI Finance Knowledge Platform - addressing the needs of the finance industry with advanced AI.
  2. Atom: AI Tools for Medical - enhancing medical research and healthcare delivery.
  3. Aica: AI Car Knowledge Platform - focusing on the automotive sector.
  4. Agni: AI Green Energy Grid - contributing to the energy sector.
  5. Alice: AI Security Infrastructure - providing solutions in the realm of security.

Despite facing understandable limitations in accessing detailed information on Graphen AI's specialized areas in small molecular drug design, nucleic acid drug design, vaccine design and optimization, and their unique approach to rare disease and patient-centric drug development, it's evident that their ambition to transform drug development is remarkably significant. This forward-thinking approach in leveraging advanced AI technologies promises to bring groundbreaking changes to the pharmaceutical landscape, heralding a new era of efficient and innovative drug discovery.

However, it's evident that their approach to drug development is innovative, leveraging AI to accelerate discovery, increase precision, and optimize formulations, thus revolutionizing the pharmaceutical industry. Graphen AI stands as a testament to the transformative power of AI in advancing various industries and improving lives.

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- Do we need Individual AI?

-Yes, we do.



The Galileo Hallucination Index represents a groundbreaking initiative in the world of artificial intelligence (AI), particularly in the field of Large Language Models (LLMs). This ongoing project aims to rigorously evaluate and rank major LLMs for their tendency to produce hallucinations - inaccurate or fabricated content - across various common task types.

Methodology Behind the Hallucination Index

1. Model Selection

Galileo's Hallucination Index encompasses a comprehensive range of LLMs, incorporating both open-source and closed-source models. The selection process involved an extensive review of current LLM repositories, industry leaderboards, and surveys. The chosen models embody the diversity in size and scope present in today's rapidly evolving LLM landscape.

2. Task Type Selection

The Index rigorously tests LLMs across three key task types:

  • Question & Answer without RAG: Evaluating the model's internal knowledge and training-based understanding.
  • Question & Answer with RAG: Assessing the model's ability to utilize external datasets, databases, or documents for accurate responses.
  • Long-Form Text Generation: Judging the model's proficiency in generating extensive, coherent text like articles, reports, or essays.

3. Dataset Selection

The Index leverages seven diverse datasets to challenge each LLM's capabilities. These datasets are meticulously chosen to represent a range of scenarios from simple Q&A to complex long-form text generation tasks.

4. Experimentation

A systematic approach to prompt formatting and generation is employed, tailored to the specific requirements of each task type. This stage is critical in ensuring the validity and reliability of the test results.

5. Evaluation and Scoring

Galileo utilizes ChainPoll for evaluation - an innovative, LLM-based methodology that focuses on the propensity for hallucinations. This method offers a nuanced perspective on model outputs, surpassing traditional statistical metrics in detecting qualitative nuances specific to the task types.

The Role of ChainPoll

ChainPoll, a methodology developed by Galileo Labs, stands at the forefront of hallucination detection in LLMs. This metric not only assesses the factual correctness of responses but also their adherence to the given context, thereby identifying both open-domain and closed-domain hallucinations.

Utilizing the Hallucination Index for LLM Selection

The Hallucination Index, while comprehensive, is not exhaustive. To address this, future plans include incorporating more models and datasets. Galileo suggests a structured approach for selecting the most appropriate model, involving task alignment, selection of top models, exploration of new models, data preparation, and performance evaluation.

Galileo, AS a notable player in the field of artificial intelligence, hascarved a niche as an engine that significantly enhances the functionality of Large Language Models (LLMs). Its primary role involves writing prompts, fine-tuning them, and crucially, removing hallucinations to ensure continuous and reliable output from AI models. Here's an elaboration on its multifaceted role:
Writing and Fine-Tuning Prompts

  1. Prompt Generation: Galileo's engine excels in creating prompts that are well-structured and tailored to elicit the most effective responses from LLMs. This involves understanding the nuances of language and the specific needs of the task at hand. 
  2. Fine-Tuning: Beyond initial prompt creation, Galileo fine-tunes these prompts during training. This process involves refining the prompts based on the model's responses, thereby increasing the accuracy and relevance of the output​​.

Removing Hallucinations  

  1. Hallucination Detection: One of the significant challenges in AI outputs is the occurrence of hallucinations – instances where the AI generates incorrect or fabricated information. Galileo addresses this by implementing advanced techniques to identify and rectify such issues. 
  2. Continuous Feedback Loop: Galileo's platform includes a monitoring module that provides a continuous feedback loop for developers. This module plays a critical role in real-time identification and correction of hallucinations, ensuring that the AI's outputs remain accurate and trustworthy​​.

Ensuring Continuous Output


Monitoring and Feedback: By integrating continuous monitoring and feedback mechanisms, Galileo ensures that the AI models it works with can provide continuous, stable, and reliable outputs. This is essential in maintaining the efficacy and reliability of AI applications in various domains​​. 

  1. Adaptability and Scalability: Galileo's approach to prompt writing and fine-tuning, coupled with its hallucination removal capabilities, ensures that AI models remain adaptable and scalable. This adaptability is crucial in a rapidly evolving AI landscape, where new challenges and requirements emerge frequently.

The Vision of Waseem Alshikh

Waseem Alshikh, the co-founder of Galileo, emphasizes the significance of overcoming hallucinations in AI models. According to Alshikh, hallucinations pose one of the biggest challenges to the rapid and effective implementation of AI in business applications. The Hallucination Index by Galileo, thus, stands as a crucial tool in mitigating this challenge and paving the way for more reliable and efficient AI deployment in various industry sectors.

In conclusion, the Galileo Hallucination Index marks a significant stride in enhancing the reliability and applicability of AI, especially in business contexts. By systematically evaluating and ranking LLMs, it provides invaluable insights into the capabilities and limitations of these models, guiding developers and enterprises in their AI implementation strategies. 


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In a digital landscape dominated by AI-driven content and algorithms, the Brave browser emerges as a refreshing alternative. While most browsers and search engines rely heavily on AI to generate and filter content, Brave is charting a different path, prioritizing unbiased information delivery and privacy.

Unveiling Brave's Approach

Brave, accessible at, stands out for its commitment to deliver information not shaped by AI algorithms. In an age where AI's influence is ubiquitous, this approach is akin to a return to traditional craftsmanship, valuing human judgment and imperfections over robotic precision.

Indexing the Web

  • Brave has impressively indexed about 20 billion pages.
  • Unlike mainstream search engines, Brave's results are not biased by advertisements, offering a cleaner information stream.

Pricing Strategy

  • Brave operates on a paid model beyond a certain usage limit.
  • After 2,000 queries per month, users pay $3 for every additional 3,000 queries.

Utilizing LLM for Clean Results

  • Surprisingly, Brave uses Large Language Models (LLMs) to refine search results.
  • This results in crisp, relevant findings, as evidenced by searches for unconventional queries like "anti-rating of Vladimir Putin," where Brave outperforms competitors like Google. I personally certify that.

Why Choose Brave?

Brave isn't just another browser; it's a gateway to a more private and unbiased online experience.

Enhanced Privacy Features

  • Brave blocks trackers and ads by default, bolstering user privacy.
  • It offers a comprehensive privacy package: ad-blocking, incognito mode, private search, and even VPN.

Easy Transition

  • Users can seamlessly switch to Brave, importing bookmarks, extensions, and passwords from their old browsers.

The Super App

  • Brave isn't limited to browsing. It offers independent search, free video calls, offline playlists, and a customizable news feed – all within the browser.

Visible Privacy

  • By blocking unwanted content, Brave ensures faster page loading, improved battery life, and data savings.

Comprehensive Protection

  • Brave surpasses other browsers in blocking invasive ads, cross-site trackers, and fingerprinting.

Advanced Customizations

  • Features like IPFS integration, Tor routing, custom filter lists, and security enhancements make Brave a highly secure browser.
  • Brave also offers a unique feature - Brave Rewards, allowing users to earn crypto tokens by opting into privacy-preserving ads.
  • The browser includes a built-in crypto wallet for managing digital assets.


A New Paradigm in Browsing

Brave represents more than just an alternative to mainstream browsers; it's a statement against the over-reliance on AI in our digital lives. It caters to those seeking a more authentic, less algorithmically-curated web experience, underlining the importance of privacy and unbiased information in the digital age.

In summary, Brave's approach offers a glimpse into a future where human judgment and privacy are valued, and where the web is a space free from the biases of targeted advertising and AI-generated content. And indeed, I utilize it.


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PAAL AI is emerging as a unique and engaging platform, especially popular among younger users. This platform allows for the creation of community bots that can interact, add content, and even summarize chats. It's a tool for those seeking to infuse their digital interactions with more convenience or to sift through conversations for meaningful insights.

Notably, PAAL AI's bots have capabilities beyond simple chat interactions. They can humorously engage with community members, even 'roasting' or 'toasting' those who deviate from community norms or narratives. This adds a layer of entertainment and engagement within the community.

One of the standout features of PAAL AI is its user-friendly bot creation process. It is designed to be accessible, even to those with no prior experience in bot development. Everything is streamlined and intuitive, ensuring that building a personal bot is as effortless as possible.

Additionally, PAAL AI has fostered a culture of sharing within its community. Users can easily share their creations, making it a collaborative and inclusive environment. This aspect is particularly appealing to those who have previously dabbled in bot creation and understand the value of community-based development and sharing.

Financially, PAAL AI is gaining traction. Its associated cryptocurrency has already seen a notable cash flow turnover, with daily volumes reaching around $3 million. This financial growth indicates a growing interest and investment in the platform's potential.

For users seeking a blend of fun, functionality, and community engagement in AI, PAAL AI presents an intriguing option. With its presence across various platforms like Twitter, GitHub, and YouTube, it's easy to dive into this ecosystem and explore all that it has to offer. Whether it's for personal use or to enhance a community experience, PAAL AI is proving to be a versatile and innovative tool in the AI landscape. Is not that cool?

BEAUTIFUL AI is revolutionizing the art of presentation-making, catering to everyone who may not have the daily need or expertise to create impactful presentations. This innovation addresses two major challenges: the reliance on individuals with specific presentation skills and the risk of producing subpar presentations that fail to captivate the audience.

Key Features of

  1. User-Friendly Design Approach: simplifies the presentation creation process, offering a wide range of smart templates that facilitate quick and impressive results.
  2. Efficiency Enhancements: By eliminating outdated steps, accelerates the transition from ideas to polished messages, organizing thoughts and bringing stories to life rapidly.
  3. Pre-Built Slides and Intuitive Controls: Hundreds of customizable slides in the slide gallery save hours that would be spent starting from scratch, and simple controls make the process seamless.
  4. Dynamic Layouts: Smart templates feature built-in layout variations, allowing for quick visualization of content in diverse formats.
  5. Community Endorsements: The platform is lauded by professionals from various fields for its ease of use and effectiveness in creating professional presentations, even for those without a design background.
  6. Focus on Productivity: is ideal for businesses seeking productivity tools and for individuals needing advanced features for online presentations.
  7. Comprehensive Template Gallery: From pitches to social media reports, the template gallery offers a starting point for a myriad of use cases.
  8. Cloud-Based Flexibility: This online tool facilitates collaboration and presentation from any location, offering compatibility with various devices and seamless export options to PowerPoint.
  9. Rich Customization and Security Features: With customizable themes, automatic animations, and robust security measures like IPFS integration and Tor routing, provides a secure and personalized experience.
  10. Team Collaboration: The Team Plan offers controls for slide, branding, and updates across a company, enhancing team efficiency.

In essence, stands out as a game-changing tool in the realm of digital presentations, marrying efficiency with aesthetics. It's a testament to the platform's ability to transform the conventional approach to presentations, making it an attractive choice for those seeking to create impactful and beautiful presentations effortlessly. Believe it or not I have become their client way before I first heard about AI Summit of 2023.


As we approach 2030, we are moving toward a profound transformation influenced by artificial intelligence. This new era will see AI playing a central role in our lives, not only in how we utilize it but also in its sophistication and development. Our daily interactions will increasingly involve AI, leading to the creation of personal avatars under our nuanced guidance. This shift will render many current professions obsolete and foster new types of business interactions. Navigating this new world will require great wisdom, both to manage these changes and to prevent potential global conflicts over resources. This transition, though challenging, opens up possibilities for human advancement and exploration beyond Earth.

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