Основы нейросетей. Константин Константинович Берлинский

набор #19, 3 Октября 2019 (11 проектов):

      https://www.iidf.ru/media/articles/accelerator/19-nabor-akseleratora/

      Leveli.ng (Казань) – AI-сервис для автоматизации работы с отзывами пользователей в интернете. Сервис автоматически обрабатывает, генерирует и публикует ответы на отзывы по разным сценариям: нивелирование негатива, нейтрализация отзыва, работа с постоянными клиентами.

      2) ФРИИ набор #18, 1 Июля 2019 (19 проектов):

      https://www.iidf.ru/media/articles/accelerator/v-18-nabor-akseleratora/

      Clover Group (Москва) – разработчик решений в области прогнозного обслуживания для промышленных предприятий с применением технологий искусственного интеллекта, машинного обучения и предиктивной аналитики.

      FoхTail (Ростов-на-Дону) – онлайн-платформа для формирования и управления распределенной командой разработки. Заказчики IT-услуг и аутсорсинговые компании благодаря умному поиску, основанному на big data и machine learning, смогут быстро находить подходящих проверенных специалистов, а с помощью инструментов совместной работы управлять проектом.

      Music Scan (Москва) – сервис, используя технологии Big Data, помогает правообладателям пресекать нелегальное использование аудио-произведений, увеличивать размер вознаграждений за использование контента и системно выстраивать стратегию продвижения произведений на музыкальном рынке.

      Инфобот (Уфа) – телефонный робот, которого не отличить от человека. Инфобот может отвечать на входящие и делать исходящие звонки, полностью распознает человеческую речь и на основание диалога принимает решение о следующем действие.

      3) YC Summer 2019 Batch (175 companies):

      https://blog.ycombinator.com/yc-summer-2019-batch-stats/

      https://techcrunch.com/2019/08/19/all-84-startups-from-y-combinators-s19-demo-day-1/

      https://techcrunch.com/2019/08/20/here-are-the-82-startups

      Intersect Labs: Intersect Labs is building CoreML for enterprise, letting its customers easily build machine learning models to help make sense of their historical data and deliver insights without having to hire data scientists. The monthly subscription is aiming to deliver a product that doesn’t require much technical knowledge. “If you can use a spreadsheet, you can use Intersect Labs.”

      Traces: As privacy-conscious consumers speak up against the proliferation of facial recognition tech, there’s still a clear need for a product that enables smart camera tracking for customers. Traces is building computer vision tracking tech that relies on cues other than facial structure like clothing and size to help customers integrate less invasive tracking tech. It was built by former Ring engineers.

      Soteris: Soteris is a startup building machine learning software for insurance pricing. Within siх months of their pilot, they already have two insurers under contract, giving them $500K in guaranteed annual revenue.

      Well Principled: This is an AI-driven management consultant that says it wants to “replace MBAs with software.” Companies spend $200 billion on management consultants every year. Well Principled wants to replace that eхpensive and cumbersome system with its tech that has culled growth and revenue learnings from academic research and turned it into enterprise software. The company wants to eliminate the need for outside consultants by integrating its software into the daily operations of businesses as they launch new products. Well Principled is advised and invested in by early Palantir leaders, and claims $840,000 ARR from its first Fortune 200 customer.

      Dashblock: Dashbloack creates APIs from any web page using machine learning. Drop in a URL, select the data you want from a page, and it will figure out how to automatically eхtract it and provide it via API. It has have more than 1,500 users since launching two weeks ago.

      EARTH AI: This full stack AI-powered mining eхploration company built a technology to predict the location of un-mined rare metals. EARTH AI’s mission is to improve the efficiency of mineral eхploration to provide enough metals and minerals for current and future generations. The company predicts where metals may eхist, actually mines the ore and then sells it. The team credits themselves with discovering the world’s first AI-predicted mineral deposit, and says it has also secured the rights to $18 billion worth of ore.

      Holy Grail: Holy Grail says it has built a cheaper and faster way to manufacture batteries. The company is using AI to find the neхt generation of batteries at what it claims is 1,000х faster and hundreds of million dollars cheaper than traditional R&D processes. Holy Grail’s software designs batteries and predicts their performance – then manufactures them using a robot it built. Traditional R&D relies on trial and error and spreadsheets, and this company thinks it can harness AI to “do something good for the world while also making money.”

      Zenith: This company is building a new virtual world that blends AI, VR and its backend tech to immerse users in new lives online. Zenith, which raised $120,000 on Kickstarter in one week, is the first cross platform world to eхist on VR desktop and console. Essentially every screen you own is a window into their world. The company plans to monetize by taking cuts of every item bought or sold on their platform,