Press Release - AI in Machine Learning

Artificial Intelligence and machine learning have been most talked topics of 2020 as both the technologies are increasingly finding their path transformed in everything from advanced quantum computing systems and consumer electronics, leading-edge medical diagnostic systems and “smart” personal assistants. According to FABRIC there was about $16.8 billion in venture capital invested in AI startups in 2019, these was 200% increase than a year before.AI is being used everywhere, from gaming stations to delivering complex information into simple at work. Scientists and Computer Engineers are working hard to communicate intelligent behavior in the machines by making them think and respond to real-time situations. AI is in transit from just a research topic to the early stages of business adoption. Tech giants like Google and Facebook have placed huge stakes on Artificial Intelligence and Machine Learning and are already using it in their products. But this is just the beginning, in the next few years, we might see AI increasingly drifting into one product following another.

Machine learning is a software application of artificial intelligence that offers organizations the capability to automatically learn and improve through experience without having to be explicitly programmed. Machine learning is focusing on the advancement of computer programs that will be able to access the data and make use of it to learn for themselves. The entire process of understanding begins with interpretations of data, such as examples, first-hand experience, or training, in order to look for patterns in information and make better decisions in the foreseeable future based on the examples that we are providing. The main objective is to permit the computers learn automatically without human intervention or help and adjust actions accordingly.

Consumer are increasing implementing cloud-based applications and services by different organizations and rising demand for intelligent virtual assistants are going to lead the growth of machine learning global market.

AI machine learning is helping organizations to understand their consumer data collected from product reviews, CRM systems, and media comments, etc., by analyzing them more efficiently. This, in turn, is helping them make better, effective, and more targeted marketing strategies. Data plays a key role in the success of a business and by helping to analyze data in a better way, AI technologies can help drive business growth.

This consumer-based use for machine learning operates primarily to smart phones and smart home devices. The voice assistants on these devices use machine learning to understand what you say and craft a response. This technology is mostly used in banks Like Kotak, HDFC, Bank of America etc. and now this automated response is also utilized in hospitals and in Siri, Google Assistant, Cortana, Amazon Alexa.

In travel industry machine learning is used and known for pricing strategy. Flights, hotels, and other travel bookings usually have a dynamic pricing strategy behind them. Consumers know that the sooner they book their trip the better, but they may not realize that the actual price changes are made via machine learning.

However, AI is a complex system and hence, requires well-trained AI experts. Limited numbers of AI experts can, therefore, slow down the adoption of AI technologies and thus, restrain the growth of the global market. Growing concerns related to data privacy can be another major challenge for the global AI technologies ecosystem.

Investments:

In 2020, launch of new technological suites and demand side investments were the key developments in this market.

For example:

Runa Capital has closed its third investment fund with $157 million to back startups in deep tech areas such as artificial intelligence and quantum computing.
Cybersecurity threat remediation provider Dtex recently announced it has raised $17.5 million. The funds will be used to expand into new and existing verticals, including banking and financial services, critical infrastructure, government, defense, pharmaceuticals, life sciences, and manufacturing.
GigaSpaces, a startup developing in-memory computing solutions for AI and machine learning workloads, last month announced it has raised $12 million.
Omilia, a startup developing natural language technologies, today announced it raised $20 million in its first ever financing round.

From Supply Side in AI machine learning providers we have companies such as NVIDIA (US), Intel (US), IBM (US), Microsoft (US), Xilinx (US), and Alphabet (US). From Demand Side in AI learning users we have companies such as Facebook, Pinterest, Twitter, Google, Edge case, Baidu HubSpot etc.

FABRIC has investigated AI in Machine learning and offers 7! cross segments. Avira's market intelligence platform FABRIC has synchronized 235 high importance market activities using Machine Learning and Data Science Algorithms. We would love to exchange our methodology, datasets, and observations on the quick demo of FABRIC.

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