Machine Learning Race: Top 15 Companies

By Jyoti Nigania |Email | Apr 20, 2018 | 7140 Views

Machine Learning is a sector which is exponentially right along with it's twin Artificial Intelligence. While the two terms are used interchangable and often together but there is a diffrence between two. AI is a large umbrella of Automation and Machine Learning  is a subset of AI that involves a program or application gatherring better knowledge of the task it is performing, based on data, without requiring it to be re-programmed. 

Here is the list of Machine Learning top 15 companies:

Amazon: 

Amazon Machine Learning is a managed service for building ML models and generating predictions, enabling the development of robust, scalable smart applications. Amazon Machine Learning enables you to use powerful machine learning technology without requiring an extensive background in machine learning algorithms and techniques.

Amazon Machine Learning combines powerful machine learning algorithms with interactive visual tools to guide you towards easily creating, evaluating, and deploying machine learning models. Its built-in data transformations ensure that input datasets can be seamlessly transformed to maximize the model's predictive quality. Once a model is built, the service's intuitive model evaluation and fine-tuning console help you understand its strengths and weaknesses, and adjust its performance to meet business objectives

The process of building ML models with Amazon Machine Learning consists of three operations:data analysis, model training, and evaluation. The data analysis step computes and visualizes your data's distribution, and suggests transformations that optimize the model training process. The model training step finds and stores the predictive patterns within the transformed data. In the optional final step, the model is evaluated for accuracy.

Apple: 

Apple has enhanced Siri, camera and quicktype with Machine Learning so it can do more than call someone in your contacts. It can now identify someone who recently emailed you but is not in your contact list like facial recognition recognized more than 30,000 Chinese Character's or shows you where you parked your car.

Google: 

Google has been on a tear, acquiring 13 companies in the past five years, to enhance visual processing, image processing, Google language, search engine ranking, speech recognition, and search prediction capabilities. In addition, it offers the Cloud AI service to customers of its Google Cloud services, allowing customers to add machine learning to their applications for things like image search and recognition, translation and voice control.

Facebook:   

Machine learning is used every day by every one of Facebook's two billion users without them realizing it. It's used for friend tagging suggestions, personalized news feed, mutual friend analysis and group recommendations for Facebook, Messenger and Instagram. The company has four AI research campuses around the world, reflecting its focus on AI for running the site.

IBM Watson: 

Watson has been around a few years but the machine learning aspect just launched last year. It allows data scientists to transform data and apply machine learning algorithms to train predictive models and build intelligent applications that leverage the predictions generated by machine learning models. Developers can also apply an algorithm to learn from data sets to generate models that can make predictions based on the data set. It also offers data model building for customers, who can choose from algorithms IBM provides or let IBM decide which is best for them.

Uber:  

To the outside world, Uber is a ride-hailing business. A machine learning-as-a-service platform that enables internal teams to seamlessly build, deploys, and operates machine learning solutions at Uber's scale. It covers end-to-end ML workflow, such as managing data, training, evaluating, and deploying models, making predictions, and monitoring predictions, such as how soon before your ride will arrive. Uber plans to eventually offer this ML as a service to the public.

Digital Reasoning:

Digital Reasoning specializes in cognitive computing to apply machine learning identifying interesting human behaviors in communications data. It uses AI to accumulate context and fill in the understanding gap from any source, resolve what's valuable and what's not, and draw conclusions based on exposing concealed relationships, risks and opportunities.

Skytree: 

Skytree speeds up machine learning methods by up to 150 times compared to open source options. Employing deeply optimized algorithms, Skytree performs analytics in-memory and utilizes the latest high performance computing techniques. By taking fewer mathematical steps to achieve the same result, Skytree has proven to be the fastest machine learning software on the market.

Qualcomm:

Qualcomm hasn't been as acquisitive as its competitors like Apple, Samsung and Intel, but it made a major move into ML with the 2017 acquisition of Dutch machine learning startup Scyfer for an undisclosed amount. Qualcomm efforts have centered around deploying artificial intelligence technology at the device level. Most of its newer Snapdragon chips have some kind of AI features designed to run on the phone, not send the computation up to the cloud. Qualcomm said it is focusing on on-device solutions to enhance reliability, cut latency and bandwidth usage and improve privacy protections. Scyfer has built AI tools for functions like revenue prediction, sound recognition for healthcare and quality inspection for manufacturing companies.

QBurst: 

QBurst pioneer among machine learning companies and artificial Intelligence companies. They apply machine learning to make data-driven decisions at a speed demanded by your business. Multidimensional problems that cannot be easily analyzed by the human brain can be resolved using a wide range of machine learning techniques. By identifying latent structures in data, revealing new insights, and making accurate predictions from data, machine learning algorithms can contextualize the information contained in huge datasets. Leveraging machine learning, you can optimize information-centric business processes, customize solutions per customer requirement, drive productivity, and forecast demand among a host of other possibilities.

N-iX:    

N-iX is something of a custom development shop, specializing in machine learning & cognitive computing expertise. It has more than 800 engineer's in-house building custom apps for customers in Healthcare, Fintech, Aviation, Information and Content Management, Entertainment, and other industries. It creates machine learning algorithms in Python & R and uses multiple additional libraries, like Caffe, DeepLearning4J, TensorFlow, Theano, Torch, and more.

AYASDI:   

Originally a DARPA-funded startup, Ayasdi was born out of Stanford├???├??├?┬╣s mathematics department. Its core technology, Topological Data Analysis, finds subtle patterns in complex data, in particular the ability to find insight in what it calls ├??├?┬ó??dark data,├??├?┬ó?? or data that was often considered to be useless but actually holds tremendous value.

Dataiku: 

Dataiku offers analytics software that enables companies to build and deliver their own data products more efficiently. Dataiku's Data Science Studio is an enterprise-grade platform for data teams that enables companies to build and deliver apps and projects using their own data more efficiently. It's meant to help data scientists be a part of the greater company team in everything from security to marketing campaigns.

LUMINOSO:   

Luminoso is one of the top artificial intelligence companies specializing in natural language understanding software. It plows through unstructured text data, from call center and chatbot transcripts to social media posts, to help companies gain insights from the conversations and feedback, as well as optimize their client interactions, detect customer trends, and discover what issues matter to customers.

Darktrace uses AI and machine learning to offer cyber security systems called Enterprise Immune System, which mimics the human immune system by learning what is 'normal' for all devices and users, updating its understanding as the environment changes, and then looks for abnormalities that could indicate security issues. Because of this it does not require the virus signatures database traditional antivirus software uses and has to constantly update as new threats are found.

Source: HOB