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Изворен канал @pythonotes · Post #401 · 15 дек.

Функция asyncio.wait() это еще один способ вызвать множество асинхронных задач. Она работает в нескольких режимах. 1. Самый простой - ждем завершения всех задач async def main(): tasks = [asyncio.create_task(do_it(i)) for i in range(10)] done, pending = await asyncio.wait( tasks, return_when=asyncio.ALL_COMPLETED ) for task in done: try: print(task.result()) except Exception as e: print(e) Очень похоже на gather, но работает не так. ▫️возвращает не результаты, а два сета с объектами Task у которых можно забрать результат через task.result() если они в списке done ▫️не гарантирует порядок результатов так как оба объекта это set ▫️не выбрасывает исключение когда оно появляется, а сохраняет его в Task. Исключение появится когда попробуете забрать резултьтат. 2. Ждем завершения первой задачи, даже если там ошибка. async def main(): tasks = [asyncio.create_task(do_it(i)) for i in range(3)] done, pending = await asyncio.wait( tasks, return_when=asyncio.FIRST_COMPLETED ) # в done может быть несколько задач! for task in done: try: print(task.result()) except Exception as e: print(f"Fail: {e}") # Оставшиеся задачи в pending, как правило, нужно отменить, иначе они будут продолжать работать for task in pending: task.cancel() В сете done будут таски которые успели завершится, причем как успешно так и нет. 3. До первой ошибки. Тоже самое, но с аргументом FIRST_EXCEPTION done, pending = await asyncio.wait( tasks, return_when=asyncio.FIRST_EXCEPTION ) Функция завершается как только первая задача упадет с ошибкой. Учтите, что в любом случае done вы можете обранужить несколько задач, как с ошибками так и успешные. ↗️ Полный листинг примеров здесь #async

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AI & Law

@ai_and_law · Post #95 · 27.08.2023 г., 08:48

🌟AI Sunday Wonders: Breakthrough in AI-Assisted Communication for Paralysis Patients Hello everybody! This Sunday we explore new studies published in Nature showcase groundbreaking advances in brain implants, offering hope to individuals with paralysis or speech impairments. Led by Dr. Jaimie Henderson and his team at Stanford Medicine, the studies highlight neuroprostheses that can decode neural activity into words on a computer screen, audio speech, or animated avatars. The implants were tested on patients like Pat Bennett, diagnosed with amyotrophic lateral sclerosis (ALS) affecting her speech. By recording neural activity during speech attempts and decoding it into words, researchers achieved promising results. A 50-word vocabulary saw a 9.1% error rate during vocalization days, and a 125,000-word vocabulary had a 23.8% error rate. These findings indicate the potential to restore fluent conversation for paralysis patients. Dr. Henderson emphasized the transformative impact on communication, with a promising future where those unable to speak can stay connected with the world. Although the studies are proof of concept and require further testing, they pave the way for future breakthroughs, offering a glimpse of technology's potential to bridge communication gaps. #AI#MedicalTech#Neuroprosthetics#Paralysis#Communication#Breakthrough#AIInnovation

Venture Village Wall 🦄

@venturevillagewall · Post #4210 · 21.02.2025 г., 16:00

Latest Funding Rounds in Tech & Agri Funding highlights: - Johnvents Industries: $40.5M - Indigenous agribusiness in Africa. Read more - Valencia Technologies: $35M - Focused on tech innovations. Read more - Certn: $30M - Efficient background screening solutions. Read more - EG 427: $28.17M - DNA medicines for chronic diseases. Read more - Methuselah: $27.46M - Medical technology advancements. Read more - Spore.bio: $23M - Innovations in microbiology. Read more - Avandra Imaging: $17.75M - Imaging technology developments. Read more - Nuveen Green Capital: $15M - Sustainable real estate financing. Read more - METYCLE: $14.71M - Supplier access and product sales. Read more - fileAI: $14M - AI file automation solutions. Read more #Funding#Agribusiness#Tech#Sustainable#BackgroundCheck#Healthcare#MedicalTech#Microbiology#RealEstate#AI

🩻From Diamond Mines to Saving Lives! South African company Lodox Systems has developed a unique full-body X-ray scanner — the Lodox Statscan. It can capture a full-body image in just 13 seconds, while delivering 10 times less radiation than a standard X-ray. 📜 The technology dates back to the 1990s, when engineers at De Beers, a diamond mining company, designed the scanner to detect diamonds being smuggled out of mines. Later, this same technology was adapted for medical use — allowing for rapid and low-dose full-body imaging in emergency situations. 📍 The first Statscan installation outside South Africa was in 2003. Today, Lodox systems are used in hospitals and trauma centers around the world. #SouthAfrica#Innovation#MedicalTech#Lodox#Radiology#TraumaCare#AfricaInTheWorld#Xray#HealthTech