What’s new in the world of artificial intelligence?

Artificial intelligence is changing the course of our lives with its constant developments. Before the pandemic and now in the new normal, AI remains to be a key trend in the tech industry. It is reaching wider audiences as years pass and scientists, engineers, and entrepreneurs who involve themselves with modern technologies are reaping the benefits of AI and its branches, IoT and machine learning.

Organizations that overlooked digital transformation and the power of artificial intelligence are picking the pace of AI adoption. When COVID-19 was creating chaos across industries, it became evident that disruptive technologies and the automation that comes with it are more than crucial.

While 2020 was a great year for artificial intelligence working with its true potential, here are the latest advancements in the field of AI that are promising exciting times for the future of this technology.

1. An AI algorithm that can predict virus spread from animals to humans

Researchers from the University of Gothenburg have found an artificial intelligence model to predict what kind of virus can possibly spread from animals to humans. Using artificial intelligence, the algorithm studies the role of carbohydrates to understand the infection path. In scientific terms, carbohydrates are called glycans and they play a significant role in the way our bodies function. Almost all viruses first affect the glycans in our bodies, so did the coronavirus. Led by Daniel Bojar, assistant professor at the University of Gothenburg, the new AI model can analyze glycans with improved accuracy. The model analyses the infection process by predicting new virus-to-glycan interactions to better understand zoonotic diseases.

2. Another AI algorithm that can outsmart hackers with fake documents

The world is evolving with disruptive technologies and that includes hackers and cyber attackers. Cyberattacks have become more common amidst the remote working culture, where sensitive files and documents have become the prime targets. To deal with this pressing concern, V.S.Subrahmanian, a cybersecurity researcher at  Dartmouth College, created an algorithm called Word Embedding-based Fake Online Repository Generation Engine (WE-FORGE) that generates fake patents that are under development. This makes it difficult for hackers to find what they are looking for. The system generates convincing fakes based on the keywords of a given document. For each keyword it identifies, it analyses a list of related topics and replaces the original keyword with one randomly chosen related word.

3. DataRobot to launch a new enterprise AI platform to leverage business and customer’s value

DataRobot announced its second major platform launch, DataRobot version 7.1 with new MLOps management agents, time series model enhancements, and automated AI reports. With an aim to provide lifecycle management for remote AI and machine learning models, DataRobot’s new launch will offer feature discovery push-down integration for Snowflake and time series Eureqa model improvements. Through this, Snowflake users can use automatic discovery and computation of individual independent variables in the Snowflake data cloud. Apart from these additions, DataRobot also provides a no-code app builder that has the ability to convert deployed models into AI apps with no coding.

4. Exscientia is leveraging AI-powered drug discovery with Allcyte’s deep learning platform

Exscientia’s US$60M acquisition of Allcyte will boost AI-drug discovery. Allcyte is an Austrian company that is developing an artificial intelligence platform to study how cancer treatments work on different individuals. Post the acquisition, this technology will work with Exscientia’s native software that uses AI to identify potential drug targets, build the right drugs, and send them for trials. Exscientia will now be able to work with a precision medicine approach to design drug molecules, ensuring improved efficiency.

5. As a relief for asset managers, Redi2 and IBM Private Cloud Services pioneering a new solution

The creator of the SaaS delivery model for financial services billing solutions, Redi2 Technologies, has announced a collaboration with IBM Private Cloud Services to improve flexibility. The combination of these technologies will add strong value for Redi2 Revenue Manager clients. Top asset managers throughout the world can take advantage of the improvements like fast reaction options for clients who need quick responses to changes, move data from one country to another or expand their infrastructure requirements.

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The report titled ‘Global Deep Learning Software Market Report,’ published by Market Expertz, gives a detailed description of each of the vital components of the market that helps in the better assessment of the present, as well as the future market situations. The report provides a thorough examination of the market, including its key opportunities and growth trends, which further enable the readers to devise business expansion strategies. The report takes the reader through a particular course of market development, simultaneously offering insights into the relevant industries, businesses, organizations, vendors, and local manufacturers.

The latest report is prepared, bearing in mind the current COVID-19 pandemic, which has severely impacted various segments of the market on both regional and global levels. The report encompasses exhaustive market research based on the post-COVID-19 market scenario for the market. Besides detailing the present and future impacts of the pandemic on the global market, the report throws light on the more efficient products and services developed by the industry participants, which thus form the basis of the competitive landscape of the global market.

The report covers extensive analysis of the key market players in the market, along with their business overview, expansion plans, and strategies. The key players studied in the report include:

Artelnics
Bright Computing
BAIR
Intel
Cognex
IBM
Keras
Microsoft
VLFeat
NIVIDA
PaddlePaddle
Torch
SignalBox
Wolfram

The global Deep Learning Software market has witnessed exponential growth on a wide scale, and certain market drivers, such as upstream raw materials, the surging population, thriving demand and supply, expanding regions, and technological advancements, have resulted in significant revenue generation. Furthermore, market history, constantly changing market scenarios, fluctuating demand and supply, and technological developments are among the other imperative factors detailed in the report.

Market Breakdown:

The market breakdown provides market segmentation data based on the availability of the data and information. The market is segmented on the basis of types and applications.

Market segment by Type, the product can be split into
Cloud based
On premise

Market segment by Application, Deep Learning Software can be split into
Large Enterprise
SMB

The report studies multiple paradigms of the global market, also including the regulations, standards, and policy changes implemented by the government on the industry over recent years. Furthermore, some of the advanced analytical tools, for instance, Porter’s Five Forces analysis and SWOT analysis, have been put to best use for delivering a comprehensive study of the global market, alongside pinpointing the fundamental market growth trends.

Focal Points of the Report:

Market Coverage: This section of the report gives a detailed account of the key manufacturers, market segments, product scope, product range, forecast period, and application landscape.
Executive Summary: This chapter focuses on the market growth rate, significant market drivers and restraints, current market trends, and competitive outlook.
Regional Analysis: This section delves into the latest import and export trends of the market, production and consumption ratio, the leading market players in each region, and revenue generation.
Manufacturers’ Portfolio: Complete portfolios of all the local and global manufacturers, along with the SWOT analysis, production value and capacity, product catalogue, and other important details of their businesses, constitute this section of the report.
Key Takeaways:

The global Deep Learning Software market report offers an in-depth study of the market’s dynamic growth patterns and sizes, the top industry players, and the important segments.
The report includes an emphasis on some of the highly valuable business priorities followed by companies across the industry in order to build on their existing business strategies.
The key highlights and recommendations in the report provide meaningful information to companies about the newest industry trends, thereby helping them strategize their long-term goals and accelerating their decision-making process.
The report further contains information on the latest market trends, driving and constraining factors, industry chain analysis, and product segmentation.

The post Future Growth Of Deep Learning Software Market By New Business Developments, Innovations, And Top Companies – Forecast To 2027 appeared first on Artificial Intelligence.