AI News

97 items

OpenAI Sep 16, 2026
This OpenAI article explains how ChatGPT Work and Codex analytics help teams understand AI usage and spend, identify training needs, and connect adoption to business outcomes.
This OpenAI article explains how ChatGPT Work and Codex analytics help teams understand AI usage and spend, identify training needs, and connect adoption to business outcomes.
How to connect AI usage to business value
This OpenAI article explains how ChatGPT Work and Codex analytics help teams understand AI usage and spend, identify training needs, and connect adoption to business outcomes.
This OpenAI article explains how ChatGPT Work and Codex analytics help teams understand AI usage and spend, identify training needs, and connect adoption to business outcomes.
Mistral AI Sep 16, 2026
Mistral and Mozilla announced a partnership in which Mistral models now power Firefox's AI browsing assistant Smart Window (beta), starting with users in France and North America and expected to reach the United Kingdom and Germany later this year, while emphasizing open distribution, fine-tuning on regional languages and dialects, conversations not saved on Mozilla's servers by default with zero data retention, and bringing sovereign AI to everyday users.
Mistral and Mozilla announced a partnership in which Mistral models now power Firefox's AI browsing assistant Smart Window (beta), starting with users in France and North America and expected to reach the United Kingdom and Germany later this year, while emphasizing open distribution, fine-tuning on regional languages and dialects, conversations not saved on Mozilla's servers by default with zero data retention, and bringing sovereign AI to everyday users.
Mistral and Mozilla Are Bringing Open, Private and Multilingual AI to Your Web Browser
Mistral and Mozilla announced a partnership in which Mistral models now power Firefox's AI browsing assistant Smart Window (beta), starting with users in France and North America and expected to reach the United Kingdom and Germany later this year, while emphasizing open distribution, fine-tuning on regional languages and dialects, conversations not saved on Mozilla's servers by default with zero data retention, and bringing sovereign AI to everyday users.
Mistral and Mozilla announced a partnership in which Mistral models now power Firefox's AI browsing assistant Smart Window (beta), starting with users in France and North America and expected to reach the United Kingdom and Germany later this year, while emphasizing open distribution, fine-tuning on regional languages and dialects, conversations not saved on Mozilla's servers by default with zero data retention, and bringing sovereign AI to everyday users.
OpenAI Sep 16, 2026
An analysis from New OpenAI Economic Research indicates that workers are using AI for purposes beyond their traditional job roles, and identifies which of these new activities become recurring parts of their work.
An analysis from New OpenAI Economic Research indicates that workers are using AI for purposes beyond their traditional job roles, and identifies which of these new activities become recurring parts of their work.
OpenAI Economic Research: How Workers Are Unlocking New Ways of Working
An analysis from New OpenAI Economic Research indicates that workers are using AI for purposes beyond their traditional job roles, and identifies which of these new activities become recurring parts of their work.
An analysis from New OpenAI Economic Research indicates that workers are using AI for purposes beyond their traditional job roles, and identifies which of these new activities become recurring parts of their work.
NVIDIA Research Sep 16, 2026
Manchester physicists David Topping and Hao Zhang, working with the NVIDIA Earth-2 team, moved generative models originally built for weather into air quality forecasting: they trained the Earth-2 CorrDiff generative downscaling model on a year of hourly UK chemistry-climate simulation data, completing training in two days on a single eight-GPU node of Isambard-AI to produce a UK-wide pollution model at 2-3 square kilometer resolution, added Earth-2 StormCast for time-dependent forecasts that directly use air quality observations, demonstrated inference and smaller training runs on the DGX Spark desktop AI system, and plan to release open source training data and workflows so other countries and regions can train their own models.
Manchester physicists David Topping and Hao Zhang, working with the NVIDIA Earth-2 team, moved generative models originally built for weather into air quality forecasting: they trained the Earth-2 CorrDiff generative downscaling model on a year of hourly UK chemistry-climate simulation data, completing training in two days on a single eight-GPU node of Isambard-AI to produce a UK-wide pollution model at 2-3 square kilometer resolution, added Earth-2 StormCast for time-dependent forecasts that directly use air quality observations, demonstrated inference and smaller training runs on the DGX Spark desktop AI system, and plan to release open source training data and workflows so other countries and regions can train their own models.
University of Manchester Uses NVIDIA Earth-2 to Forecast Air Pollution Across the UK
Manchester physicists David Topping and Hao Zhang, working with the NVIDIA Earth-2 team, moved generative models originally built for weather into air quality forecasting: they trained the Earth-2 CorrDiff generative downscaling model on a year of hourly UK chemistry-climate simulation data, completing training in two days on a single eight-GPU node of Isambard-AI to produce a UK-wide pollution model at 2-3 square kilometer resolution, added Earth-2 StormCast for time-dependent forecasts that directly use air quality observations, demonstrated inference and smaller training runs on the DGX Spark desktop AI system, and plan to release open source training data and workflows so other countries and regions can train their own models.
Manchester physicists David Topping and Hao Zhang, working with the NVIDIA Earth-2 team, moved generative models originally built for weather into air quality forecasting: they trained the Earth-2 CorrDiff generative downscaling model on a year of hourly UK chemistry-climate simulation data, completing training in two days on a single eight-GPU node of Isambard-AI to produce a UK-wide pollution model at 2-3 square kilometer resolution, added Earth-2 StormCast for time-dependent forecasts that directly use air quality observations, demonstrated inference and smaller training runs on the DGX Spark desktop AI system, and plan to release open source training data and workflows so other countries and regions can train their own models.
NVIDIA Technical Blog Sep 16, 2026
In this technical article, NVIDIA explains how NVLink 6 supports large-scale AI factories through a multi-layer resiliency framework spanning the physical, link, application, and system layers: the physical layer combines lightweight FEC with Physical Layer Retry (PLR) and UPHY recovery for a natively lossless fabric, the link layer uses credit-based flow control (CBFC) to eliminate packet drops by design, and the application layer uses Dynamo Shadow Engine Recovery and checkpointing to shorten interruptions, with the article reporting that in benchmarked deployments on B200 GPUs shadow engine recovery reduced inference downtime from 283 seconds to 7.3 seconds.
In this technical article, NVIDIA explains how NVLink 6 supports large-scale AI factories through a multi-layer resiliency framework spanning the physical, link, application, and system layers: the physical layer combines lightweight FEC with Physical Layer Retry (PLR) and UPHY recovery for a natively lossless fabric, the link layer uses credit-based flow control (CBFC) to eliminate packet drops by design, and the application layer uses Dynamo Shadow Engine Recovery and checkpointing to shorten interruptions, with the article reporting that in benchmarked deployments on B200 GPUs shadow engine recovery reduced inference downtime from 283 seconds to 7.3 seconds.
NVIDIA details NVLink 6 multi-layer resiliency: physical-layer correction plus Dynamo shadow engine cut inference downtime from 283 seconds to 7.3 seconds
In this technical article, NVIDIA explains how NVLink 6 supports large-scale AI factories through a multi-layer resiliency framework spanning the physical, link, application, and system layers: the physical layer combines lightweight FEC with Physical Layer Retry (PLR) and UPHY recovery for a natively lossless fabric, the link layer uses credit-based flow control (CBFC) to eliminate packet drops by design, and the application layer uses Dynamo Shadow Engine Recovery and checkpointing to shorten interruptions, with the article reporting that in benchmarked deployments on B200 GPUs shadow engine recovery reduced inference downtime from 283 seconds to 7.3 seconds.
In this technical article, NVIDIA explains how NVLink 6 supports large-scale AI factories through a multi-layer resiliency framework spanning the physical, link, application, and system layers: the physical layer combines lightweight FEC with Physical Layer Retry (PLR) and UPHY recovery for a natively lossless fabric, the link layer uses credit-based flow control (CBFC) to eliminate packet drops by design, and the application layer uses Dynamo Shadow Engine Recovery and checkpointing to shorten interruptions, with the article reporting that in benchmarked deployments on B200 GPUs shadow engine recovery reduced inference downtime from 283 seconds to 7.3 seconds.
IBM Research Sep 15, 2026
The work proposes a theoretical separation between quantum computers and large language models, noting that recent research further demonstrates the theoretical abilities of quantum computing, but the loaded text contains only the title and a one-sentence summary without specific methods, proofs, or results.
The work proposes a theoretical separation between quantum computers and large language models, noting that recent research further demonstrates the theoretical abilities of quantum computing, but the loaded text contains only the title and a one-sentence summary without specific methods, proofs, or results.
A theoretical separation between quantum computers & LLMs
The work proposes a theoretical separation between quantum computers and large language models, noting that recent research further demonstrates the theoretical abilities of quantum computing, but the loaded text contains only the title and a one-sentence summary without specific methods, proofs, or results.
The work proposes a theoretical separation between quantum computers and large language models, noting that recent research further demonstrates the theoretical abilities of quantum computing, but the loaded text contains only the title and a one-sentence summary without specific methods, proofs, or results.
OpenAI Sep 14, 2026
Fyxer uses OpenAI models, fine-tuning, memory, and real user feedback to organize inboxes and draft emails in each user's own voice.
Fyxer uses OpenAI models, fine-tuning, memory, and real user feedback to organize inboxes and draft emails in each user's own voice.
How Fyxer built an AI executive assistant people trust
Fyxer uses OpenAI models, fine-tuning, memory, and real user feedback to organize inboxes and draft emails in each user's own voice.
Fyxer uses OpenAI models, fine-tuning, memory, and real user feedback to organize inboxes and draft emails in each user's own voice.