AI News, 25 Machine Learning Startups To Watch In 2019 artificial intelligence

Top 25 Machine Learning Startups Companies To Watch In 2019

There are 8,705 startups and companies listed in Crunchbase today who are relying on machine learning for their main and ancillary applications, products, and services.83% of machine learning startups Crunchbase tracks have had just three funding rounds or less with seed, angel and early-stage rounds being the most common.Artificial Intelligence-related companies raised $9.3B in 2018, a 72% increase over 2017, according to PwC/CB Insights MoneyTree Report, Q4 2018.Artificial intelligence deals increased in Q1, 2019 to 116 deals, up from 104 deals in Q4, 2018 according to the latest PwC/CB Insights MoneyTree Report Q1 2019.AI-based marketing patents are the fasting growing global category, reaching a Compound Annual Growth Rate (CAGR) of 29.3% between 2010 and 2018, according to EconSight.From powering personalized career sites that recommend open positions that are ideal for a given candidate based on their capabilities as eightfold.ai does today, to scaling the complexity and volume of machine learning algorithms, so they're more accessible as DataRobot does, machine learning startups are taking on many of business' most significant challenges.

Please see the latest roundup of machine learning forecasts and market estimates, 2019 for more market data on machine learnings' exponential growth.25 Machine Learning Startups To Watch In 2019Alation - Alation offers a machine learning data catalog to help people find, understand, and trust data across their organizations.

Their latest funding was raised on Jan 17, 2019, from a Series C round.Anodot - Capitalizes on the innate strengths of machine learning by continually looking for patterns using constraint-based modeling across the diverse data sets, businesses are relying on to operate daily.

Anodot's Autonomous Analytics platform leverages advanced machine learning techniques to constantly analyze and correlate every business parameter, providing real-time alerts and forecasts, in their context, lowering time to detection and resolution.

The following screen from their app is an example of how Anodot provides real-time anomaly detection.Ablacon - Ablacon is a fascinating startup that has built a premier machine intelligence system to quantitatively and qualitatively understand and treat atrial fibrillation (AF).Their technology visualizes in real-time what is going on in the heart.

This was a Series A round raised on Apr 30, 2019, with Ajax Health.Biofourmis - Biofourmis is a fast-growing global digital health tech start-up that is reinventing remote patient monitoring by combining AI, machine learning, and real-time monitoring.

Their Biovitals platform is one of the most sophisticated personalized physiological data analytics engine based on human physiology that formulates personalized health models, resulting in highly optimized post-acute patient monitoring solutions and accurate prediction of patient health deterioration before it happens.

The startup has raised a total of $41.6M in funding over six rounds, the latest being on May 21, 2019, from MassMutual Ventures, and Sequoia Capital India.Cinnamon - One of the most exciting machine learning startups to watch based on their unique approach to integrating AI techniques and machine learning to streamline the mundane tasks of automating data extraction from unstructured documents, Cinnamon has shown steady progress in the last year gaining new customers and adding new features to their solution.

Their Falcon platform stops breaches by detecting all attacks types, even malware-free intrusions, providing five-second visibility across all current and past endpoint activity while reducing cost and complexity for customers.

Their latest funding was raised on Nov 30, 2017, from a Series C round led by Nvidia and Wells Fargo.HEALTH[at]SCALE - What fascinating about this startup is how it is developing machine learning and artificial intelligence solutions for health care's most challenging problems, including matching every patient to appropriate treatment by relevant providers at the best time for patients to achieve optimal results.

This was a Series A round raised on May 17, 2019, led by Optum.Hunters.AI - What makes this startup unique in the rapidly growing field of AI and machine learning-based cybersecurity startups is the approach to provide real-time updates on Attack Intelligence, Hunting AI, and continuous automation with an enterprise's existing security data.

This was a Seed round raised on May 22, 2019, led by Blumberg Capital and YL Ventures.Impact Analytics - Capitalizing on the inherent strengths of AI and machine learning to find anomalies, patterns and trends in legacy data and entirely new data sets from recently launched business models is where Impact Analytics makes its most significant contributions.

Impact Analytics has raised a total of $750K in a Seed round raised on Oct 31, 2016, led by Aarin Capital.Innovaccer - Innovaccer develops AI- and machine learning-based systems for healthcare organizations, enabling them to integrate complex data across multiple distributed sources and provide valuable insights to healthcare professionals.

Their latest funding was raised on Sep 22, 2015, from a Series A round led by Paytm.People.ai - One of the most creative, insightful startups in revenue management, People.ai helps sales, marketing, and customer success teams uncover every revenue opportunities from every customer.

Their latest funding was raised on May 20, 2019, from a Series B round.RAVIN - Using AI, machine learning and traffic monitoring cameras to gather a continuous real-time stream of data that is used to analyze a vehicles' current condition, RAVIN provides greater transparency to rental car companies, fleet owners and user car sales networks.AI and machine learning are used to evaluate and immediately report any anomalies in the condition of a vehicle.

A conceptual representation of their vehicle reporting is shown below:Senso.ai - Created to serve financial service providers by helping them manage and grow their consumer credit portfolios, Senso.ai is a leading cloud-based AI platform in the financial services industry.

This was a Series A round raised on May 16, 2019.Tamr - Following the success of initial research at MIT Computer Science and Information Lab (CSAIL), the Tamr team began building a commercial-grade solution designed to tackle the challenge of connecting and enriching diverse data at scale using machine learning.

Their latest funding was raised on Sep 18, 2018.Terramonitor - Terramonitor gives professionals the power to analyze, build, and organize geographical information into actionable insights by leveraging up-to-date satellite data, AI, and machine learning.

As a result of their unique approach to data capture combined with advanced AI and machine learning analysis of imagery, Terramonitor can quickly analyze broad geographic regions for agricultural, infrastructure, environmental, and forestry-related insights.

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From powering personalized career sites that recommend open positions that are ideal for a given candidate based on their capabilities as eightfold.ai does today, to scaling the complexity and volume of machine learning algorithms, so they’re more accessible as DataRobot does, machine learning startups are taking on many of business’ most significant challenges.

Forbes lists 25 machine learning startups to watch in 2019, including NextAI alumni venture Senso.ai.Created to serve financial service providers by helping them manage and grow their consumer credit portfolios, Senso.ai is a leading cloud-based AI platform in the financial services industry.

From powering personalized career sites that recommend open positions that are ideal for a given candidate based on their capabilities as eightfold.ai does today, to scaling the complexity and volume of machine learning algorithms, so they’re more accessible as DataRobot does, machine learning startups are taking on many of business’ most significant challenges.

Vroom! F1 Racing Game Offers First Crypto Collectable

F1 Delta Time, a blockchain-based racing game, has just launched a new line of crypto collectables including “Cars, Drivers, and Components.”

However, “fungible Tokens (FTs) based on the ERC-20 token standard will function as a currency in the game, and will be equally necessary as they will be used in transactions such as paying entry fees and purchasing certain items,”

While I doubt many will want to buy a virtual car for 360 ETH, it’s clear there is some sort of real or imaginary demand for these products.

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