Quote of the Day: Prowling Neighbor a City Thought It Shed
'Did they walk over the Golden Gate Bridge? That's my top theory.'
CHRISTINE WILKINSON, a carnivore ecologist at the University of California, Santa Cruz, on the mystery of coyotes re-emerging in San Francisco in the early 2000s after vanishing for 75 years.
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Entrepreneur
2 hours ago
- Entrepreneur
Researchers develop more efficient language model control method
A team of researchers has successfully developed a more efficient method to control the outputs of large language models (LLMs), addressing one of the key challenges in artificial intelligence text... This story originally appeared on Calendar A team of researchers has successfully developed a more efficient method to control the outputs of large language models (LLMs), addressing one of the key challenges in artificial intelligence text generation. The breakthrough enables more effective guidance of LLMs to produce text that adheres to specific structures while maintaining accuracy. The new approach focuses on controlling language model outputs to adhere to predetermined structures, such as programming languages, while eliminating errors that commonly plague AI-generated content. This advancement represents a significant step forward in making AI language tools more reliable for specialized applications. Improving Structural Adherence in AI Text Generation The research addresses a fundamental issue with large language models: their tendency to generate text that deviates from required formats or contains errors when tasked with producing structured content. By implementing more effective control mechanisms, the researchers have developed a system that maintains structural integrity throughout the generation process. For programming languages specifically, this advancement could reduce the frequency of syntax errors and logical flaws that often appear in code generated by AI systems. The method ensures that the language model adheres to the programming language's rules while generating functional code. Technical Approach and Implementation While specific technical details of the method were not fully outlined, the approach appears to involve guiding the language model's generation process more precisely than previous methods. Rather than simply prompting the model and hoping for correctly structured output, the new system actively steers the generation process to maintain compliance with predefined rules. This control mechanism works by: Monitoring the model's outputs in real-time Applying constraints that keep text generation within acceptable parameters Correcting potential errors before they appear in the final output Practical Applications The improved control method opens up new possibilities for utilizing large language models in fields that require strict adherence to specific formats. Some potential applications include: Software Development: Generating error-free code that adheres to the syntax rules of specific programming languages can make AI coding assistants more reliable for developers. Data Formatting: Creating structured data outputs like JSON, XML, or CSV files with perfect adherence to format specifications. Technical Documentation: Producing documentation that follows industry-standard formats without introducing structural errors. Scientific Research: Generating properly formatted research papers or reports that adhere to publication guidelines. Future Research Directions This advancement likely represents an early step in a broader effort to make large language models more controllable and reliable. Future research may expand on this work by: Developing more sophisticated control mechanisms that can handle increasingly complex structural requirements. Reducing the computational overhead associated with implementing these controls, making them more accessible for wider use. Extending the approach to handle multiple types of structured outputs simultaneously. The research highlights the growing focus on not just making AI language models more powerful, but also more precise and controllable. As these systems become increasingly integrated into professional workflows, the ability to guarantee structured, error-free outputs becomes critical. For industries that rely on structured data and formatted text, this development may signal a shift toward more practical and reliable AI assistance tools that can consistently follow rules while maintaining the creative and analytical capabilities that make large language models valuable. The post Researchers develop more efficient language model control method appeared first on Calendar.
Washington Post
2 hours ago
- Washington Post
In wake of deep cuts, NOAA says it will hire for 'mission-critical' weather service positions
The National Oceanic and Atmospheric Administration said Monday it will hire for 'mission-critical field positions' amid expert warnings that the National Weather Service has been cut too sharply just as hurricane season arrives. An agency spokesperson said in a statement the positions will be advertised under a temporary reprieve from the federal government's widespread hiring pause 'to further stabilize frontline operations.' NOAA also said they are filling some field office openings by reassigning staff, including some temporary hires. The agency didn't say how many jobs would be posted and refused to provide more details. Elon Musk's Department of Government Efficiency cuts gutted NWS and NOAA — which provide daily weather forecasts, up-to-the-minute severe storm warnings, climate monitoring and extreme weather tracking — earlier this year. Hundreds of weather forecasters were fired and other federal NOAA employees were put on probationary status in February, followed by a later round of more than 1,000 cuts at the agency . By April, nearly half of NWS forecast offices had 20% vacancy rates . The Federal Emergency Management Agency has also been affected. The new hires would be seen by the scientific community as especially imperative as the agency predicts a busy hurricane season and more tornados . In recent years, greenhouse gas emission-driven climate change has fueled more frequent, deadly, costly and increasingly nasty storms . The weather service's mission includes warning people in danger with enough time to evacuate or find safe shelter. The cuts forced weather forecast offices to reduce their hours or no longer staff overnight shifts in less critical periods. Insiders and experts have warned of the consequences that a staffing shortage would mean for weather forecasting amid extreme weather and the U.S. economy . 'In 2024, NOAA was able to offer some of its most accurate weather forecasting to date for active hurricanes,' said Union of Concerned Scientists science fellow Marc Alessi. 'These incredibly accurate forecasts were made possible by a fully funded NOAA. 'Despite the worsening climate and extreme weather impacts being felt across the country, the Trump administration has proceeded with its inhumane agenda that will leave people on the frontlines of disasters at greater risk,' Alessi added. ___ Alexa St. John is an Associated Press climate reporter. Follow her on X: @alexa_stjohn . Reach her at . ___ Read more of AP's climate coverage at ___ The Associated Press' climate and environmental coverage receives financial support from multiple private foundations. AP is solely responsible for all content. Find AP's standards for working with philanthropies, a list of supporters and funded coverage areas at .
Associated Press
3 hours ago
- Associated Press
In wake of deep cuts, NOAA says it will hire for 'mission-critical' weather service positions
The National Oceanic and Atmospheric Administration said Monday it will hire for 'mission-critical field positions' amid expert warnings that the National Weather Service has been cut too sharply just as hurricane season arrives. An agency spokesperson said in a statement the positions will be advertised under a temporary reprieve from the federal government's widespread hiring pause 'to further stabilize frontline operations.' NOAA also said they are filling some field office openings by reassigning staff, including some temporary hires. The agency didn't say how many jobs would be posted and refused to provide more details. Elon Musk's Department of Government Efficiency cuts gutted NWS and NOAA — which provide daily weather forecasts, up-to-the-minute severe storm warnings, climate monitoring and extreme weather tracking — earlier this year. Hundreds of weather forecasters were fired and other federal NOAA employees were put on probationary status in February, followed by a later round of more than 1,000 cuts at the agency. By April, nearly half of NWS forecast offices had 20% vacancy rates. The Federal Emergency Management Agency has also been affected. The new hires would be seen by the scientific community as especially imperative as the agency predicts a busy hurricane season and more tornados. In recent years, greenhouse gas emission-driven climate change has fueled more frequent, deadly, costly and increasingly nasty storms. The weather service's mission includes warning people in danger with enough time to evacuate or find safe shelter. The cuts forced weather forecast offices to reduce their hours or no longer staff overnight shifts in less critical periods. Insiders and experts have warned of the consequences that a staffing shortage would mean for weather forecasting amid extreme weather and the U.S. economy. 'In 2024, NOAA was able to offer some of its most accurate weather forecasting to date for active hurricanes,' said Union of Concerned Scientists science fellow Marc Alessi. 'These incredibly accurate forecasts were made possible by a fully funded NOAA. 'Despite the worsening climate and extreme weather impacts being felt across the country, the Trump administration has proceeded with its inhumane agenda that will leave people on the frontlines of disasters at greater risk,' Alessi added. ___ Alexa St. John is an Associated Press climate reporter. Follow her on X: @alexa_stjohn. Reach her at [email protected]. ___ Read more of AP's climate coverage at ___ The Associated Press' climate and environmental coverage receives financial support from multiple private foundations. AP is solely responsible for all content. Find AP's standards for working with philanthropies, a list of supporters and funded coverage areas at
