Analytics Vidhya

OCTOBER 13, 2024

AI is becoming more accessible, and one of the most exciting advancements is the release of OpenAI o1 on ChatLLM Teams. This powerful AI model can significantly boost your productivity by offering a wide range of tools, from generating creative content to solving complex technical problems. Best of all, you don’t need a premium subscription […] The post How to Access OpenAI’s o1 Models Without a Premium Subscription?

OpenAI 171

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Marktechpost

OCTOBER 13, 2024

Large language models (LLMs) have made significant progress in language generation, but their reasoning skills remain insufficient for complex problem-solving. Tasks such as mathematics, coding, and scientific questions continue to pose a significant challenge. Enhancing LLMs’ reasoning abilities is crucial for advancing their capabilities beyond simple text generation.

Large Language Models 114

Large Language Models LLM AI AI 114

Artificial Lawyer

OCTOBER 13, 2024

Baker McKenzie’s well-known Innovation Product Manager, Cem Ucan, is joining Leya, the genAI startup, to help drive the change he wants to see happen in.

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Marktechpost

OCTOBER 13, 2024

Mixture of Experts (MoE) models are becoming critical in advancing AI, particularly in natural language processing. MoE architectures differ from traditional dense models by selectively activating subsets of specialized expert networks for each input. This mechanism allows models to increase their capacity without proportionally increasing the computational resources required for training and inference.

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Machine Learning Research at Apple

OCTOBER 13, 2024

Optimal transport (OT) has profoundly impacted machine learning by providing theoretical and computational tools to realign datasets. In this context, given two large point clouds of sizes nnn and mmm in Rdmathbb{R}^dRd, entropic OT (EOT) solvers have emerged as the most reliable tool to either solve the Kantorovich problem and output a n×mntimes mn×m coupling matrix, or to solve the Monge problem and learn a vector-valued push-forward map.

Machine Learning 52

Machine Learning 52

Pickl AI

OCTOBER 13, 2024

Summary: Selecting the right Data Science Bootcamp is crucial for your career. Evaluate curriculum quality, instructor expertise, job placement support, flexibility, and costs to make an informed decision that aligns with your professional goals. Introduction In today’s data-driven world, Data Science has emerged as a crucial field across various industries, enabling businesses to make informed decisions and drive innovation.

Data Science 52

Data Science Machine Learning Data Analysis Python 52

Marktechpost

OCTOBER 13, 2024

Robotic task execution in open-world environments presents significant challenges due to the vast state-action spaces and the dynamic nature of unstructured settings. Traditional robots struggle with unexpected objects, varying environments, and task ambiguities. Existing systems, often designed for controlled or pre-scanned environments, lack the adaptability required to respond effectively to real-time changes or unfamiliar tasks.

Robotics 78

Robotics LLM Categorization Automation 78

Pickl AI

OCTOBER 13, 2024

Summary: Types of Artifical Intelligence based on functionalities: Reactive Machines, which respond to current inputs; Limited Memory AI, which learns from past data; Theory of Mind AI, which understands human emotions; and Self-Aware AI, which possesses consciousness. Each type plays a unique role in AI applications. Introduction What if machines could think, learn, and adapt like humans?

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Categorization Chatbots 52

Marktechpost

OCTOBER 13, 2024

Large language models (LLMs) have demonstrated impressive capabilities in in-context learning (ICL), a form of supervised learning that doesn’t require parameter updates. However, researchers are now exploring whether this ability extends to reinforcement learning (RL), introducing the concept of in-context reinforcement learning (ICRL). The challenge lies in adapting the ICL approach, which relies on input-output pairs, to an RL framework that involves input-output-reward triplets.

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Speaker: Anindo Banerjea, CTO at Civio & Tony Karrer, CTO at Aggregage

When developing a Gen AI application, one of the most significant challenges is improving accuracy. This can be especially difficult when working with a large data corpus, and as the complexity of the task increases. The number of use cases/corner cases that the system is expected to handle essentially explodes. 💥 Anindo Banerjea is here to showcase his significant experience building AI/ML SaaS applications as he walks us through the current problems his company, Civio, is solving.

Generative AI

Robot Writers AI

OCTOBER 13, 2024

Red Flag: Google’s CoHosted-Podcast Maker Not Always Accurate Google’s new NotebookLM — which has gone viral with its ability to auto-script and auto-produce a co-hosted podcast in minutes — is unfortunately also very good at making things up. The new AI research tool — which uses two, extremely natural-sounding robot voices to discuss text, audio or video that you input into NotebookLM — is currently wowing the Web.

AI Engineer 52

AI Engineer Robotics ChatGPT Generative AI 52

Marktechpost

OCTOBER 13, 2024

One of the most pressing challenges in the evaluation of Vision-Language Models (VLMs) is related to not having comprehensive benchmarks that assess the full spectrum of model capabilities. This is because most existing evaluations are narrow in terms of focusing on only one aspect of the respective tasks, such as either visual perception or question answering, at the expense of critical aspects like fairness, multilingualism, bias, robustness, and safety.

Automation 72

Automation ML Computer Vision AI 72

TheSequence

OCTOBER 13, 2024

Created Using Ideogram Next Week in The Sequence: Edge 439: Our series about state space models continues with a review of Zamba, a model that combines SSMs and attention layers. We review the original Zamba paper published by the Zyphra team and LitServe framework for model serving. Edge 440: We discuss EUREKA, a recent foundation model evaluation framework published by Microsoft.

AI 52

AI AI Machine Learning ML Engineer 52

Marktechpost

OCTOBER 13, 2024

Large language models (LLMs) often fail to consistently and accurately perform multi-step reasoning, especially in complex tasks like mathematical problem-solving and code generation. Despite recent advancements, LLMs struggle to detect and learn from errors because they are predominantly trained on correct solutions. This limitation leads to difficulties in verifying and ranking outputs, particularly when subtle flaws are present.

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AI Research AI Researcher LLM Large Language Models 70

Speaker: Brendan Sweeney, VP of Sales & Devyn Blume, Sr. Account Executive

Are you curious about how artificial intelligence is reshaping sales coaching, learning, and development? Join Brendan Sweeney and Devyn Blume of Allego for an engaging new webinar exploring AI's transformative role in sales coaching and performance improvement! Brendan and Devyn will share actionable insights and strategies for integrating AI into coaching and development - ensuring personalized, effective, and scalable training!

AI

Extreme Tech

OCTOBER 13, 2024

Doing this might void the warranty of your Raspberry Pi 5, but the results could be amazing.

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Marktechpost

OCTOBER 13, 2024

The current challenges in text-to-speech (TTS) systems revolve around the inherent limitations of autoregressive models and their complexity in aligning text and speech accurately. Many conventional TTS models require complex elements such as duration modeling, phoneme alignment, and dedicated text encoders, which add significant overhead and complexity to the synthesis process.

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ML Artificial Intelligence Artificial Intelligence AI 64

ODSC - Open Data Science

OCTOBER 13, 2024

Editor’s note: Dr. Einat Orr is a speaker for ODSC West this October 29th-31st. Be sure to check out her talk, “ Don’t Go Over the Deep End: Building an Effective OSS Management Layer for Your Data Lake ,” there! Managing a data lake can often feel like being lost at sea — especially when dealing with both structured and unstructured data. Join Dr. Einat Orr, at 11:35 on October 30th at ODSC West where she will guide you through that storm, offering a high-level overview of tools and strategies

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Metadata Data Science Artificial Intelligence Artificial Intelligence 40

Eleuther.ai

OCTOBER 13, 2024

Interim report on ongoing work on mechanistic anomaly detection

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Marktechpost

OCTOBER 13, 2024

Model merging is an advanced technique in machine learning aimed at combining the strengths of multiple expert models into a single, more powerful model. This process allows the system to benefit from the knowledge of various models while reducing the need for large-scale individual model training. Merging models cuts down computational and storage costs and improves the model’s ability to generalize to different tasks.

Machine Learning 102

Machine Learning AI AI ML 102

Marktechpost

OCTOBER 13, 2024

Automatic benchmarks like AlpacaEval 2.0, Arena-Hard-Auto, and MTBench have gained popularity for evaluating LLMs due to their affordability and scalability compared to human evaluation. These benchmarks use LLM-based auto-annotators, which align well with human preferences, to provide timely assessments of new models. However, high win rates on these benchmarks can be manipulated by altering output length or style, even though measures have been developed to control these factors.

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LLM Automation ChatGPT ML 119

Marktechpost

OCTOBER 13, 2024

Recent progress in LLMs has spurred interest in their mathematical reasoning skills, especially with the GSM8K benchmark, which assesses grade-school-level math abilities. While LLMs have shown improved performance on GSM8K, doubts remain about whether their reasoning abilities have truly advanced, as current metrics may only partially capture their capabilities.

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Machine Learning LLM ML Artificial Intelligence 116