Training foundation models, such as GPT-3 and PaLM, can be extremely expensive, often involving tens of thousands of GPUs running continuously for months. These models are typically trained in specialized clusters featuring fast, homogeneous interconnects and using carefully designed software systems that support both data parallelism and model/pipeline parallelism. Such dedicated clusters can be costly and difficult to obtain. Can we instead leverage the much greater amount of decentralized, heterogeneous, and lower-bandwidth interconnected compute? Previous works examining the heterogeneous, decentralized setting focus on relatively small models that can be trained in a purely data parallel manner. State-of-the-art schemes for model parallel foundation model training, such as Megatron, only consider the homogeneous data center setting. In this paper, we present the first study of training large foundation models with model parallelism in a decentralized regime over a heterogeneous network. Our key technical contribution is a scheduling algorithm that allocates different computational "tasklets" in the training of foundation models to a group of decentralized GPU devices connected by a slow heterogeneous network. We provide a formal cost model and further propose an efficient evolutionary algorithm to find the optimal allocation strategy. We conduct extensive experiments that represent different scenarios for learning over geo-distributed devices simulated using real-world network measurements. In the most extreme case, across 8 different cities spanning 3 continents, our approach is 4.8X faster than prior state-of-the-art training systems (Megatron).

Machine learning analysis of stool samples may provide a helpful first pass for the mass screening for any type of cardiovascular disease (CVD) in patients, researchers claimed. Various machine learning algorithms were fed gut microbiota data and, with training, were subsequently able to distinguish between people with and without CVD, with ROC curves as high as 0.70, reported a group led by Sachin Aryal, an MS student in bioinformatics at the University of Toledo, Ohio. "While this demonstrates the promising potential of applying microbiome-based ML [machine learning] for predicting CVD, in the future, it will be of interest to further calibrate and improve predictive capability of ML modeling by including more samples from different sources or stratifying specific types of CVD incorporated with combinatorial features such as health records, in addition to gut microbiome data," the authors said. Their study was presented as a poster at the virtual Hypertension meeting, sponsored by the American Heart Association, and was simultaneously published online in the November 2020 issue of Hypertension. Investigators claimed theirs as the first study to apply existing knowledge of dysbiosis of gut microbiota in CVD patients to a machine learning approach to CVD screening.

A blue-collar worker is a working class person who performs manual labor. Blue-collar work may involve skilled or unskilled manufacturing, mining, sanitation, custodial work, textile manufacturing, power plant operations, farming, commercial fishing, landscaping, pest control, food processing, oil field work, waste disposal, recycling, electrical, plumbing, construction, mechanic, maintenance, warehousing, shipping, technical installation, and many other types of physical work. Blue-collar work often involves something being physically built or maintained. In contrast, the white-collar worker typically performs work in an office environment and may involve sitting at a computer or desk. A third type of work is a service worker (pink collar) whose labor is related to customer interaction, entertainment, sales or other service-oriented work.

Scientific studies do not find any links between video games and gun violence. Yet on Monday, US president Donald Trump insisted that "gruesome and grisly video games" were causative in the gun massacre deaths of 22 people in El Paso and another 9 in Dayton (not Toledo) Ohio. Why scapegoat video games and demonise the people who play them? You know, that restrictions on the purchase of guns in America are so lax, you can just walk in and buy one at Walmart, a local store, a gun show or from a friend or neighbour. Trump has heavy investment in that laxity.

TOLEDO, Ohio (AP) - No longer a novelty, drones are becoming an everyday tool for more police and fire departments, new research has found. The number of public safety agencies with drones has more than doubled since the end of 2016, according to data collected by the Center for the Study of the Drone at New York's Bard College. The center estimated that just over 900 police, sheriff, fire and emergency agencies now have drones, with Texas, California, and Wisconsin leading the way, the study showed. While many law enforcement drone units are just getting started and are in place in just a fraction of the public safety agencies around the country, police and fire departments are continuing to find new uses for the remote-controlled aircraft. They're being deployed to take photos of car accidents, guide firefighters through burning buildings and search for missing people and murder suspects.

TOLEDO, OHIO – No longer a novelty, drones are becoming an everyday tool for more police and fire departments, new research has found. The number of public safety agencies with drones has more than doubled since the end of 2016, according to data collected by the Center for the Study of the Drone at New York's Bard College. The center estimated that just over 900 police, sheriff, fire and emergency agencies now have drones, with Texas, California, and Wisconsin leading the way, the study showed. While many law enforcement drone units are just getting started and are in place in just a fraction of the public safety agencies around the country, police and fire departments are continuing to find new uses for the remote-controlled aircraft. They're being deployed to take photos of car accidents, guide firefighters through burning buildings and search for missing people and murder suspects.

In the spring of 1960, just after he turned 16, Chuck Stout went to work as a "garbage boy" at a McDonald's in Toledo, Ohio.

TOLEDO, OHIO – Satellites in space and a robot under Lake Erie's surface are part of a network of scientific tools trying to keep algae toxins out of drinking water supplies in the shallowest of the Great Lakes. It's one of the most wide-ranging freshwater monitoring systems in the U.S., researchers say, and some of its pieces soon will be watching for harmful algae on hundreds of lakes nationwide. Researchers are creating an early warning system using real-time data from satellites that in recent years have tracked algae bloom hotpots such as Florida's Lake Okeechobee and the East Coast's Chesapeake Bay. The plan is to have it in place within two years so that states in the continental U.S. can be alerted to where toxic algae is appearing before they might detect it on the surface, said Blake Schaeffer, a researcher with U.S. Environmental Protection Agency. "You don't have to wait until someone gets sick," said Schaeffer, one of the leaders of the project.

TOLEDO, Ohio – Police say a 14-year-old Ohio girl told them she fatally shot her 15-year-old brother after they fought over a video-game system and he repeatedly hit her in the face. A Lucas County Juvenile Court judge on Wednesday found sufficient probable cause to charge the girl with murder in the December shooting death of her brother. The Associated Press generally doesn't identify juveniles charged with crimes. Toledo police Detective Jeff Clark testified the girl told him that her brother hit her in the face so many times before the shooting that it felt like she was being hit with a baseball bat. Prosecutors have filed a motion to transfer the case to adult court.