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Zhipu AI Introduces GLM-4 Model: Next-Generation Foundation Model Comparable with GPT-4
Zhipu AI unveiled GLM-4 in Beijing, a new model addressing challenges in Large Language Models. It supports a 128k token context length, achieving nearly 100% accuracy with long inputs and introducing the GLM-4 All Tools for autonomous complex task execution. Its multimodal capabilities and versatility make it a competitive choice for businesses, challenging existing models…
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The rise of “liar’s dividend” as AI-generated deep fakes continue to trouble
The rise of AI-generated deep fakes, known as “liar’s dividend,” is troubling as it impacts politics, society, and individuals. Deep fakes can distort truth and manipulate public perception, with experts struggling to reliably differentiate real from fake content. Efforts to curb deep fakes have been ineffective, raising concerns about the destabilization of truth.
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Innovative AI tool CognoSpeak promises faster dementia diagnosis
CognoSpeak, developed by the University of Sheffield, is an AI tool for faster dementia and Alzheimer’s diagnosis. It analyzes speech patterns and cognitive tests, demonstrating accuracy comparable to traditional assessments. The tool is undergoing broader trials in UK memory clinics and shows potential to reduce waiting times and provide early treatment. AI supports neurological disorders…
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Researchers from UCLA, University of Washington, and Microsoft Introduce MathVista: Evaluating Math Reasoning in Visual Contexts with GPT-4v, BARD, and Other Large Multimodal Models
MathVista is introduced as a comprehensive benchmark for mathematical reasoning in visual contexts. It amalgamates challenges from various multimodal datasets, aiming to refine mathematical reasoning in AI systems. Researchers from UCLA, University of Washington, and Microsoft extensively evaluate foundation models and highlight the potential of GPT-4V in achieving a state-of-the-art accuracy of 49.9%.
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This Machine Learning Paper from DeepMind Presents a Thorough Examination of Asynchronous Local-SGD in Language Modeling
This text discusses the advancements in language modeling through the use of large language models (LLMs) and the challenges faced in optimizing these models for distributed training. It introduces an innovative asynchronous method that combines delayed Nesterov momentum updates and dynamic local updates, showcasing significant improvements in training efficiency for language models.
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Few companies apply New York’s new automated AI hiring law
New York City enacted Law 144, regulating automated employment decision tools (AEDTs) to combat biases in hiring. The law requires auditing for bias, transparency notices, and sets fines for non-compliance. However, researchers from Cornell University found low compliance due to vague definitions and employer discretion. This raises questions about its effectiveness in addressing bias in…
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What’s next for robotaxis in 2024
The promise of robotaxis seemed imminent in 2023, but it came crashing down after tragic accidents involving Cruise, suspending its operations in California. While other companies like Waymo and Baidu continue their robotaxi services, challenges such as high costs, scalability issues, and safety concerns persist. The industry is poised for significant changes in 2024, but…
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Why does AI being good at math matter?
Google DeepMind recently created AlphaGeometry, an AI system combining a language model and a symbolic engine to solve complex geometry problems, demonstrating progress in AI reasoning skills. However, human understanding of technology is crucial to harness AI’s potential, as argued by Conrad Wolfram. AI is also being deployed to address racial segregation in South Africa…
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FDA approves DermaSensor’s AI skin cancer detector
The FDA approved DermaSensor’s AI-powered handheld skin cancer detector for US sale. Skin cancer, a common and fatal disease, often goes undetected. DermaSensor’s non-invasive device uses ESS to detect skin cancer with 96% accuracy and will be available through a subscription model. It aims to aid PCPs in making referrals to dermatologists and reduce unnecessary…
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CMU Research Introduces CoVO-MPC (Covariance-Optimal MPC): A Novel Sampling-based MPC Algorithm that Optimizes the Convergence Rate
Model Predictive Control (MPC) is widely used in fields such as power systems and robotics. A recent study from Carnegie Mellon University focused on the convergence characteristics of a sampling-based MPC technique called Model Predictive Path Integral Control (MPPI). The research led to the development of a new method called CoVariance-Optimal MPC (CoVO-MPC), which outperformed…