AI Developments: Report #1
- Johnny Shollaj
- Technology, Data
- 14 Aug, 2023
The main highlights for (Aug 7, 2023 - Aug 14, 2023) include :
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NVIDIA recent developments, including GH200 Grace Hopper Superchip Platform & AI Workbench
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Google's Project IDX and AdaTape Foundation Model
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Hugging Face Support for Swift & BentoML Integration
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Langchain & Github Repositories supporting the "Interactive Simulacra of Human Behavior" paper
Below we have a breakdown of the filtered articles, tutorials, papers and guides!
General News
The Guardian: A Tsunami of AI Misinformation Will Shape Next Year’s Knife-Edge Elections
Summary: "The upcoming 2024 elections in various democratic countries, especially the US, are facing the threat of AI-generated misinformation that can significantly impact the results. With the advancements in AI tools like ChatGPT and others, creating and spreading false information has become easier and more convincing. The consequences of a manipulated election could be significant, potentially leading to a drastic change in US governance. Despite awareness of this threat, practical solutions seem lacking, as academia and tech companies grapple with the challenge."
Key Takeaway: "AI-enabled misinformation poses a serious risk to the integrity of global elections, particularly in 2024, with the potential to tip the balance in crucial votes. The need for robust mechanisms to counteract this threat is urgent, but current efforts may be hampered by technological interests and lack of decisive action from platform owners."
John Naughton | The Guardian
Publication Date: August 12, 2023
Venture Beat: Machine unlearning: The critical art of teaching AI to forget
Summary: Machine unlearning is an emerging field in AI that focuses on teaching algorithms to "forget" or erase specific datasets. This process is crucial when algorithms are trained on outdated, incorrect, or private data. However, current methods for machine unlearning are costly and time-consuming, and a complete solution has not yet been found. Recent research and competition, such as Google's machine unlearning challenge, are making progress towards effective unlearning methods. Businesses are urged to implement strategies to align with legal and ethical standards and to keep pace with machine unlearning as a part of responsible AI practice.
Key Takeaway: Machine unlearning presents both a significant opportunity and challenge for businesses, particularly concerning privacy, security, and ethics. The growing demand for this capability has sparked research and investment, but solutions are still in development. A comprehensive understanding and implementation of machine unlearning practices will be essential for businesses employing large datasets and AI models, impacting how organizations manage data handling, compliance, and adapt to the dynamic nature of AI and ML.
Matthew Duffin | Venture Beat
Publication Date: August 12, 2023
Neuro Science News: AI Pinpoints Parkinson’s Subtypes Using Stem Cell Images
Summary: Researchers at the Francis Crick Institute, in collaboration with UCL Queen Square Institute of Neurology and Faculty AI, have successfully used machine learning to predict four Parkinson’s disease subtypes using stem cell images. This achievement, with top accuracies reaching 95%, could lead to more personalized treatments and targeted drug development for Parkinson’s patients.
Key Takeaway: The utilization of AI to classify Parkinson's disease subtypes enables the potential for highly tailored treatments. By identifying specific subtypes through the examination of mitochondria and lysosomes within cells, this groundbreaking technique opens doors to personalized medicine and new drug discovery, significantly impacting the future of Parkinson’s disease care and research.
Clare Green | Francis Crick Institute
Publication Date: August 11, 2023
India Express: What is Project IDX, Google’s new AI-integrated coding environment?
Summary: Google has launched Project IDX, an innovative integrated development environment (IDE) aimed at transforming app development. By utilizing AI and cloud technologies, it provides a web-based workspace for multiplatform full-stack development, making app creation more accessible and efficient for developers.
Key Takeaway: Project IDX is set to impact the developer community substantially by providing a “super IDE” equipped with unique features like Codey, an AI coding bot, and support for popular frameworks and languages. Built on Visual Studio Code, it enables seamless creation of applications for various platforms and integrates smart features for code suggestions. Google's move aligns with the trend of leveraging AI in development and is indicative of potential collaboration and competition within the tech industry, positioning Project IDX as a significant step towards making app development more effortless and intuitive.
Bijin Jose | India Express
Publication Date: August 13, 2023
Coin Telegraph: Anthropic cracks open the black box to see how AI comes up with the stuff it says
Summary: Artificial intelligence research organization Anthropic has published significant research focusing on how large language models (LLMs) like Claude, ChatGPT, and Google's Bard generate their outputs. The study aims to understand if these models rely on "memorization" or whether there is a more complex relationship between training data, fine-tuning, and the eventual outputs.
Key Takeaway: Anthropic's research delves into the complex workings of large language models (LLMs) to understand how they generate outputs, uncovering that these models don't rely solely on memorization of training data. By using a top-down approach with statistical analysis called "influence functions," the study sheds light on the multifaceted interaction within different AI layers. Although currently limited to pre-trained models, this research serves as a foundational step towards a more profound comprehension of neural network functions and may extend to more advanced models in the future.
Tristan Greene | Coin Telegraph
Publication Date: August 10, 2023
Research Blogs
MIT News: AI model can help determine where a patient’s cancer arose
Researchers at MIT and Dana-Farber Cancer Institute have developed a machine-learning model called OncoNPC that analyzes the genetic sequence of 400 genes to predict the origin of a tumor in the body. This approach can accurately classify at least 40% of previously unidentifiable tumors, enabling a 2.2-fold increase in patients eligible for targeted treatment. The model has the potential to guide doctors towards personalized treatments, and the team plans to expand the model to include other data types for a more comprehensive prediction.
Key Takeaway: The OncoNPC model can significantly improve treatment options for patients with cancers of unknown primary origin, enabling more precise and effective therapies. By guiding treatment decisions, it may enhance survival rates and quality of life for cancer patients. The model's development marks a promising step towards integrating AI in medical diagnostics and patient care, setting a precedent for future advancements in personalized medicine.
Anne Trafton | MIT News
Publication Date: August 7, 2023
NVIDIA: SIGGRAPH Special Address: NVIDIA CEO Brings Generative AI to LA Show
The key highlights from the latest NVIDIA conference are the following:
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GH200 Grace Hopper Superchip Platform: Superchip platform aiming to help various data centers accelerate AI computations and expand memory and bandwidth, for faster more efficient processing.
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NVIDIA AI Workbench: Introducing simplified AI model tuning, it democratizes generative AI development, enabling businesses to quickly adapt and scale AI applications.
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NVIDIA Omniverse Upgrades: Enhancing virtual world creation with generative AI, it encourages collaboration and enables seamless interaction with 3D pipelines. The integration of OpenUSD adds universal compatibility across tools.
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New Desktop Systems and Servers: These will fuel AI, graphics, real-time rendering, and industrial digitalization, paving the way for future content creation and processing demands.
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Collaboration with Industry Leaders: Partnerships, such as with Hugging Face, will foster generative AI development and accessibility.
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Research Innovations: Demonstrations of AI-powered materials for 3D scenes and advanced video conferencing capabilities showcase a future where AI offers fine creative control and immersive communication experiences.
Key Takeaway: NVIDIA recent development shows that AI and graphics are inseparable, with a potential to revolutionize diverse sectors like entertainment, healthcare, manufacturing, and communication.
Brian Caulfield | NVIDIA
Publication Date: August 8, 2023
Google: AdaTape: Foundation model with adaptive computation and dynamic read-and-write
Research Summary:
Adaptive computation is about a machine learning system adjusting its behavior based on the complexity of the input, rather than using a fixed function like conventional neural networks. AdaTape is a new model that takes this to the next level by using dynamic sets of tokens to create elastic input sequences. It offers better performance in various tasks, and more efficiency compared to other adaptive models. Its innovative approaches, such as an adaptive tape reading mechanism and a unique "tape bank," make it a promising breakthrough in the field.
Potential Impact:
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Enhanced Efficiency: By tailoring computation based on input complexity, AdaTape can allocate resources more judiciously, improving the performance-to-cost ratio. This could result in significant savings in processing time and computational resources.
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Increased Accuracy: AdaTape offers the ability to dynamically adjust its approach to processing data. This adaptability allows it to outperform conventional and existing adaptive models in specific challenging tasks, such as image classification and algorithmic tasks.
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New Solutions to Old Problems: AdaTape's inductive bias makes it capable of solving problems that were previously out of reach for other models. For example, it successfully tackled the parity task, a problem that standard transformers could not solve.
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Wider Application Scope: With its flexibility and efficiency, AdaTape could be implemented across a range of applications, from complex data analysis to real-time adaptive systems, making it a versatile tool for different industry needs.
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Alignment with Hardware: Unlike some adaptive models, AdaTape's architecture is well-suited to current hardware accelerators like TPUs. This compatibility ensures that businesses can harness its full potential without major hardware investments.
Key Takeaway: As industries move towards more real-time and complex decision-making, the need for adaptive, efficient, and intelligent machine learning models grows. AdaTape answers this call by providing a mechanism that is not only more adaptable to varying complexities but also optimizes the tradeoff between quality and cost. By leveraging AdaTape, businesses can achieve higher accuracy, greater efficiency, and more innovative solutions, aligning with the ever-growing demands of the digital age. This makes AdaTape a valuable asset in maintaining a competitive edge in today's rapidly evolving technological landscape.
Fuzhao Xue, Mostafa Dehghani | Google
Publication Date: August 8, 2023
AWS: Amazon Translate enhances its custom terminology to improve translation accuracy and fluency
Amazon Translate's neural machine translation service has introduced enhancements to its custom terminology, focusing on domain-specific and language-specific customizable translations. These updates allow for context-sensitive match and replace, preserving sentence constructs, and improving translation quality and fluency.
The new enhancements cater to government and commercial organizations, providing flexibility in translating unique content such as brand names, model names, and character names. The system recognizes context, gender, plurality, verb tense, and noun forms to create more nuanced translations.
Examples include translating "tutor" with gender specificity in French, inflecting plurality for the word "sheep," or using the correct verb tense for "walking."
The update requires no changes for existing customers, and detailed instructions for creating and using custom terminology files are provided.
Key Takeaway From a business perspective, this precision ensures that translations resonate more accurately with specific audiences, enhancing global communication and reducing the risk of misunderstandings. This can lead to more effective marketing, international relations, and customer service, ultimately having a positive impact on the bottom line.
Sathya Balakrishnan, Sid Padgaonkar | AWS
Publication Date: August 11, 2023
Microsoft Azure: Scale generative AI with new Azure AI infrastructure advancements and availability
Summary: Microsoft Azure has made critical advancements in AI infrastructure, positioning generative AI as a transformative force across multiple industries. They've announced the global expansion of Azure OpenAI Service, making GPT-4 and GPT-3.5-Turbo available in new regions. The ND H100 v5 Virtual Machine series, equipped with NVIDIA H100 GPUs, has now been released to cater to complex AI workloads. This expansion enhances Azure's offerings, enabling users to build next-generation, AI-powered applications and providing businesses with unparalleled generative AI capabilities.
Key Takeaway: The latest advancements in Azure's AI infrastructure underscore the commitment to scaling AI capabilities worldwide, allowing for faster and more effective deployment of AI solutions. For businesses, this means increased efficiency, innovation, and adaptability in areas ranging from manufacturing to financial services. These enhancements align with the growing global demand for robust, scalable AI, setting the stage for a new era of innovation that can shape various industries. Leveraging Azure’s expanded infrastructure can be a strategic move for businesses aiming to gain a competitive edge through AI-driven solutions.
Nidhi Chappell, Eric Boyd | Azure
Publication Date: August 7, 2023
Research Papers
Evaluating the performance of large language models: ChatGPT and Google Bard in generating differential diagnoses in clinicopathological conferences of neurodegenerative disorders
Summary: This study evaluated the use of large language models (LLMs), specifically ChatGPT-3.5, ChatGPT-4, and Google Bard, in predicting neuropathological diagnoses from clinical summaries for 25 cases of neurodegenerative disorders at the Mayo Clinic. The models' predictions were compared to the final clinical diagnoses made by physicians. The primary diagnoses were correct in 32% of cases for ChatGPT-3.5, 52% for ChatGPT-4, and 40% for Google Bard. Correct diagnoses were included among the multiple diagnoses in 76% of cases for ChatGPT-3.5, 84% for ChatGPT-4, and 76% for Google Bard
Key Takeaway: The results highlight the potential of LLMs like ChatGPT in neuropathology, especially in facilitating comprehensive discussions in clinicopathological conferences.
Shunsuke Koga, Nicholas B. Martin, Dennis W. Dickson
Publication Date: August 8, 2023
Contextualized Knowledge Graph Embedding for Explainable Talent Training Course Recommendation
Summary: The paper introduces a novel approach called Contextualized Knowledge Graph Embedding (CKGE) for personalized employee training course recommendations. CKGE integrates both neighbor semantics and high-order connections to model individual learning motivations, using a unique KG-based Transformer (KGformer). Through relational attention, structural encoding, and path prediction, CKGE aims to provide precise and explainable recommendations. Extensive experiments on real-world datasets support the method's effectiveness and interpretability.
Key Takeaways:
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Innovative Approach: CKGE offers a fresh perspective on course recommendations by considering complex learning motivations.
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Explainability: The integration of knowledge graphs and special attention mechanisms ensures transparent, meaningful recommendations.
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Precision: The method promises accurate predictions for course preferences tailored to individual needs.
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Relevance: CKGE aligns with the trend of leveraging data-driven paradigms in talent management, having potential high impact in personalized learning and development within enterprises.
Yang, Zhang, Song, Dong, Zhu, Li
Publication Date: August 8, 2023
Large-scale Urban Cellular Traffic Generation via Knowledge-Enhanced GANs with Multi-Periodic Patterns
Summary: The paper proposes a knowledge-enhanced GAN (Generative Adversarial Network) for generating large-scale urban cellular traffic, essential for 5G network planning. This novel model simulates multi-periodic patterns and long-term aperiodic dynamics, capturing urban environmental influences through a knowledge graph (KG). Extensive experiments demonstrate a substantial performance improvement of over 32.77% compared to state-of-the-art models, with urban knowledge contributing 4.71% enhancement. Generalization and robustness across different urban areas also affirm the model's utility.
Key Takeaways:
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Innovative Model: The introduction of a GAN model with urban knowledge graphs allows for accurate simulation of long-term cellular traffic, capturing both periodic and aperiodic patterns.
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Urban Environment Integration: By considering various urban factors, the model effectively tailors cellular traffic predictions to specific urban dynamics.
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Significant Performance Improvement: With over 32% improvement compared to existing models and a further 4.71% from urban knowledge enhancement, the method exhibits superior fidelity.
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Generalization & Application: Demonstrated effectiveness across different urban areas and potential applicability to other traffic types such as website visiting and urban passenger traffic supports the model's broader relevance and scalability.
Hui, Wang, Yang, Feng, Zhu, Deng, Hui
Publication Date: August 8, 2023
Development
Hugging Face: Hugging Face Platform on the AWS Marketplace: Pay with your AWS Account
Summary: The Hugging Face Platform is now available on the AWS Marketplace, allowing AWS customers to pay for Hugging Face services directly through their AWS accounts. This integration simplifies the payment process for services like Inference Endpoints, Spaces Hardware Upgrades, and AutoTrain, facilitating easier access to popular machine learning models. The subscription process is outlined for users, ensuring seamless connectivity between AWS and Hugging Face accounts.
Key Takeaway: This new integration between Hugging Face and AWS removes financial and administrative barriers, making it more convenient for businesses to adopt AI technologies. By centralizing billing through the AWS account, companies can efficiently manage payments for all Hugging Face services, fostering easier collaboration and utilization of machine learning models like Llama 2, StarCoder, or BERT. The identical pricing to public Hugging Face pricing, billed through AWS, streamlines the adoption process for developers and organizations.
Simon Brandeis, Philipp Schmid, Jeff Boudier
Publication Date: August 10, 2023
Hugging Face: Releasing Swift Transformers: Run On-Device LLMs in Apple Devices
Summary: A slew of updates and tools were released today to support text generation in Swift, including the new swift-transformers package and the swift-chat app. Tools for Core ML conversion, like exporters and transformers-to-coreml, have been updated and some converted models like Llama 2 7B or Falcon 7B are ready for use. The details cover multiple aspects of conversion to Core ML, optimization techniques, tokenization, and more, including specific coding instructions.
Key Takeaway: The release is a comprehensive step forward for Swift developers working with text generation and Core ML models, making the conversion and optimization process more streamlined and flexible. With support for different tokenization methods, abstraction of complex processes, and focus on optimization techniques, these updates enhance efficiency and provide a foundation for developers to work with different models and generation algorithms, offering an engaging platform for ongoing improvements and innovations.
Pedro Cuenca
Publication Date: August 8, 2023
Hugging Face: Deploying Hugging Face Models with BentoML: DeepFloyd IF in Action
Summary: The article details how to deploy Hugging Face models, such as the DeepFloyd IF text-to-image model, using BentoML, an open-source platform for machine learning model serving and deployment. It walks through defining, saving, and deploying the model, and outlines how to use DeepFloyd IF in BentoML. Detailed instructions for preparing the environment, scaling runners, and building a deployable Bento are provided, including specific code and command examples.
Key Takeaway: BentoML offers a comprehensive solution for deploying Hugging Face models like DeepFloyd IF in a production-ready manner. The article guides users step-by-step through the process, making it accessible even for those new to the platform. The capability of BentoML to handle various ML frameworks, along with its ease of use and integration with tools like Docker and Kubernetes, makes it a powerful tool for real-world deployment and scaling of AI applications.
Sherlock Xu , Zhao Shenyang
Publication Date: August 9, 2023
GitHub: Generative Agents: Interactive Simulacra of Human Behavior
Summary: The research paper titled "Generative Agents: Interactive Simulacra of Human Behavior" has been accompanied by a repository containing a core simulation module for generative agents that simulate human behaviors. The repository includes detailed instructions for setting up the simulation environment locally, running, replaying, and demoing a simulation, as well as customizing simulations through authoring agent history or creating new base simulations. There are specific directions for generating necessary files, installing requirements, starting servers, and utilizing different commands to interact with the simulations, providing a comprehensive guide for interacting with the generative agents in the game environment of Smallville.
Park, O'Brien, Cai, Morris, Liang, Bernstein
GitHub: FaceChain
Summary: FaceChain is a deep-learning toolchain designed to generate a digital twin using a single portrait photo. It enables users to create personal photos in various settings and is powered by ModelScope, offering compatibility with various Python and GPU configurations. Recent updates include resolving a GPU memory issue, adding a depth parameter to git clone to shorten download time, and providing installation guides for Docker, notebooks, and a detailed description of the algorithm's training and inference stages.
GitHub: FaceChain
Summary: FaceChain is a deep-learning toolchain designed to generate a digital twin using a single portrait photo. It enables users to create personal photos in various settings and is powered by ModelScope, offering compatibility with various Python and GPU configurations. Recent updates include resolving a GPU memory issue, adding a depth parameter to git clone to shorten download time, and providing installation guides for Docker, notebooks, and a detailed description of the algorithm's training and inference stages.
Langchain: GPT Researcher x LangChain
Summary: LangChain has integrated with GPT Researcher, a leading open-source research assistant, to enhance web research using Large Language Models (LLMs). The integration provides easy access to various LLM models and facilitates seamless logging with LangSmith, a debugging/logging/monitoring platform. LangChain believes that this collaboration represents a significant opportunity for LLMs and sees it as part of the future, with a focus on complex but targeted applications.
Langchain: Villagers x LangSmith: Simulating multi-agent social networks with LangSmith
Summary: The Villagers team collaborated with LangSmith to create a proof-of-concept for simulating multi-agent social networks, particularly mimicking real Twitter users' interactions. By utilizing LangSmith's capabilities, they were able to automate traces, quickly iterate on prompts, and efficiently debug for this complex scenario, including testing community responses to ad campaigns, political statements, and social commentary. The use of LangSmith significantly sped up development time and enhanced the confidence in the quality of the prompts in a system that required managing a large number of agents running in parallel.
Langchain: NeumAI x LangChain: Efficiently maintaining context in sync for AI applications
Summary: NeumAI and LangChain have collaborated to enhance AI applications by maintaining context synchronously and efficiently, especially for data that constantly changes like team documentation. They have introduced scheduling and orchestration to the ingestion pipeline, utilizing LangChain text splitters. Neum automatically synchronizes the source data with the vector store, ensuring up-to-date context, and uses efficient vectorizing technology to reduce costs, all of which can be applied to large-scale AI applications like chatbots to make them more accurate and responsive.
Practical Tutorials and Resources
Building a RCI Chain for Agents with LangChain Expression Language -
Sam Witteveen
LangSmith From LangChain | Building production-grade LLM Apps -
Data Science Basics
Now in AI: Handpicked by Better Programming -
Various Medium Authors
Introducing ModelFusion: Build AI apps with JavaScript and TypeScript -
Lars Grammel
