stork
Wood storks to be removed from federal Endangered Species List
But the only native stork found in the U.S. is not out of the woods just yet. Breakthroughs, discoveries, and DIY tips sent six days a week. After over 40 years of recovery efforts, one population of the wood stork ()is being removed from the federal list of endangered and threatened wildlife. The large birds are as tall as 45 inches with wingspans that can reach 65 inches and are the only native storks in the United States. They are primarily found in the southeastern United States, where they feed on fish.
- North America > United States > Georgia (0.30)
- North America > United States > Texas (0.06)
- North America > United States > North Carolina (0.06)
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- Law > Environmental Law (0.49)
- Media > Photography (0.36)
Can AI make novels better? Not if these attempts are anything to go by
Feedback is New Scientist's popular sideways look at the latest science and technology news. You can submit items you believe may amuse readers to Feedback by emailing feedback@newscientist.com One of the great joys in life, Feedback argues, is the perfect opening sentence of a book – and the concomitant realisation that, yes, this one is going to be good. "It was the day my grandmother exploded." "As the manager of the Performance sits before the curtain on the boards and looks into the Fair, a feeling of profound melancholy comes over him in his survey of the bustling place."
LlamaDuo: LLMOps Pipeline for Seamless Migration from Service LLMs to Small-Scale Local LLMs
Park, Chansung, Jiang, Juyong, Wang, Fan, Paul, Sayak, Tang, Jing
The widespread adoption of cloud-based proprietary large language models (LLMs) has introduced significant challenges, including operational dependencies, privacy concerns, and the necessity of continuous internet connectivity. In this work, we introduce an LLMOps pipeline, "LlamaDuo", for the seamless migration of knowledge and abilities from service-oriented LLMs to smaller, locally manageable models. This pipeline is crucial for ensuring service continuity in the presence of operational failures, strict privacy policies, or offline requirements. Our LlamaDuo involves fine-tuning a small language model against the service LLM using a synthetic dataset generated by the latter. If the performance of the fine-tuned model falls short of expectations, it is enhanced by further fine-tuning with additional similar data created by the service LLM. This iterative process guarantees that the smaller model can eventually match or even surpass the service LLM's capabilities in specific downstream tasks, offering a practical and scalable solution for managing AI deployments in constrained environments. Extensive experiments with leading-edge LLMs are conducted to demonstrate the effectiveness, adaptability, and affordability of LlamaDuo across various downstream tasks.
- Europe > United Kingdom (0.28)
- North America > United States > Hawaii (0.04)
- North America > United States > Arizona (0.04)
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Storks refine their migration routes as they learn from experience
White storks take increasingly quicker and more direct routes for their migrations as they get older, which suggests they learn by experience to perfect these paths. "We've been able to track these animals and gain detailed information on when and where they go," says Ellen Aikens at the University of Wyoming. "But we wanted to learn more about how migration is refined and developed over the stork's lifetime." White storks (Ciconia ciconia) mostly breed in Europe, but fly to central or southern Africa for the winter. Between 2013 and 2020, Aikens and her colleagues captured 258 juvenile white storks at five breeding sites in Germany and Austria.
- Europe > Germany (0.29)
- North America > United States > Wyoming (0.27)
- Europe > Austria (0.27)
- Africa > Southern Africa (0.27)
Real AI for the Workaday World
Artificial intelligence might one day be used to power genuinely humanlike cyborgs or other figments of humanity's fertile imagination. For now, Ingo Stork is using the technology to help restaurant chains waste less food and do more with fewer workers. Dr. Stork is co-founder of PreciTaste, a startup that uses AI-based sensors and algorithms to accomplish one fairly specific task: predict how much food people will order at any given moment, and make sure that it's being prepared in a timely fashion.
What AI still can't do
Machine-learning systems can be duped or confounded by situations they haven't seen before. A self-driving car gets flummoxed by a scenario that a human driver could handle easily. An AI system laboriously trained to carry out one task (identifying cats, say) has to be taught all over again to do something else (identifying dogs). In the process, it's liable to lose some of the expertise it had in the original task. Computer scientists call this problem "catastrophic forgetting."
- South America > Brazil > Rio de Janeiro > Rio de Janeiro (0.05)
- North America > United States > Massachusetts > Middlesex County > Cambridge (0.05)
- Europe > Germany (0.05)
- Health & Medicine > Therapeutic Area > Oncology (0.71)
- Health & Medicine > Therapeutic Area > Hematology (0.49)
AI Could Scan IVF Embryos to Help Make Babies More Quickly
If a woman (or non-female identifying person with a uterus and visions of starting a family) is struggling to conceive and decides to improve their reproductive odds at an IVF clinic, they'll likely interact with a doctor, a nurse, and a receptionist. They will probably never meet the army of trained embryologists working behind closed lab doors to collect eggs, fertilize them, and develop the embryos bound for implantation. One of embryologists' more time-consuming jobs is doing something called "grading" embryos--looking at their morphological features under a microscope and assigning a quality score. Round, even numbers of cells are good. They'll use that information to decide which embryos to implant first. Newer methods, like pulling off a cell to extract its DNA and test for abnormalities, something called preimplantation genetic screening, provide more information.
British Army testing autonomous vehicles to supply frontline troops Internet of Business
Drones and other unmanned systems are to be tested on Salisbury Plain by the British military, to tackle the costly and often dangerous task of delivering essential supplies to frontline troops. One such company is Animal Dynamics, a spinout from Oxford University. The startup has turned to recent advances in computational analysis to help it learn from nature and challenge engineering conventions. By tapping into design lessons from millions of years of evolution, Animal Dynamics is producing machines that mirror the mechanics of animals to help them perform better and move more efficiently. The Financial Times reports that Stork, the firm's autonomous paraglider, is one of five unmanned transport concepts chosen by the British government's Defence, Science and Technology Laboratory for assessment during a four-week military exercise on Salisbury Plain this November. The Stork consumes less fuel than a conventional drone and can carry up to 100kg of supplies over 100km.
The algorithms of No Man's Sky - Rambus
This entry was posted on Tuesday, May 17th, 2016. Developed and published by the indie studio Hello Games, 'No Man's Sky' is built around a procedurally generated deterministic open universe that contains a staggering 18.4 quintillion planets. The game also boasts complete solar systems, varied weather systems, detailed flora and fauna, fascinating alien creatures, as well as fully functioning buildings and spacecraft. Indeed, No Man's Sky plots the position of stars and their stellar classification, while pseudorandom numbers generated from the position of each star are used to determine the planetary system and corresponding features. "The universe begins with a single input, an arbitrary numerical seed--the phone number of one of the programmers. That number is mathematically mutated into more seeds by a cascading series of algorithms--a computerized pseudo-randomness generator," Roc Morin of The Atlantic explained in a detailed article about the game.
Lipreading by neural networks: Visual preprocessing, learning, and sensory integration
Wolff, Gregory J., Prasad, K. Venkatesh, Stork, David G., Hennecke, Marcus
Automated speech recognition is notoriously hard, and thus any predictive source of information and constraints that could be incorporated into a computer speech recognition system would be desirable. Humans, especially the hearing impaired, can utilize visual information - "speech reading" - for improved accuracy (Dodd & Campbell, 1987, Sanders & Goodrich, 1971). Speech reading can provide direct information about segments, phonemes, rate, speaker gender and identity, and subtle information for segmenting speech from background noise or multiple speakers (De Filippo & Sims, 1988, Green & Miller, 1985). Fundamental support for the use of visual information comes from the complementary nature of the visual and acoustic speech signals. Utterances that are difficult to distinguish acoustically are the easiest to distinguish.
- North America > United States > California > San Mateo County > Menlo Park (0.05)
- North America > United States > New York (0.04)
- North America > United States > California > Santa Clara County > Stanford (0.04)