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Tag: ML (page 1 of 8)

IISc, Kotak Mahindra Bank ties up to set up AI ML Centre in Bengaluru

The Indian Institute of Science and Kotak Mahindra Bank have tied up to set up an Artificial Intelligence – Machine Learning Centre at the IISc campus in Bengaluru. It will offer bachelor’s, master’s, and short-term courses in AI, ML, Natural Language processing, and similar areas. The Bank has funded the center as part of the CSR initiative, as it will also promote research and innovation in AI-ML.

IBM Watson launches new AI, automation features

IBM has announced new AI and Automation capabilities in IBM Watson, that will make customer care easy for businesses across all channels – phone, web, SMS, etc. The features include a collaboration with IntelePeer, a communication platform-service provider, to set up a new voice agent, seamless switching to live agent with problem context. This means customers don’t have to repeat their problems to a human representative.

Source: CXO Today

New Report says Facebook in process of developing ML Chips

Facebook is developing a Machine Learning chip with capabilities to handle content recommendations to users, said a report by The Information. Another chip for video transcoding has already been developed by Facebook, the report elaborated. The move comes amidst a time when tech giants like Apple, Google, etc. are choosing to develop their own chips, instead of relying on external providers to save on cost and time.

TCS, Wipro, 3 others to implement data analytics project at  SEBI

Five companies – TCS, Wipro, Capgemini, L&T Infotech, and NEC Corp India – have been shortlisted by SEBI for the implementation of data analytics projects. In an effort to address and handle challenges arising out of technological advances in markets, selected firms are expected to build analytical models with AI and ML. Then, the analytical development will be done according to regulator SEBI’s requirement.

Source: The Hindu

Mphasis will focus on these four pillars for growth in FY22

Mphasis CEO Nitin Rakesh said the company would continue to focus on expanding its capabilities, regional presence, leadership, and building a portfolio of IP-driven AI/ML innovation. Mphasis hired around 2,000 people for each of the previous two quarters, and the company aims to keep employing in India and other countries where it has fulfillment centers. The international expansion entails reaching out to new markets for both talent and business.

Nokia, Vodafone launch cloud-based ML-powered network anomaly detection service

Nokia and Vodafone have launched a service that detects and remediates network anomalies. The service, running on the Google cloud, is an ML-powered product that is expected to detect 80% of Vodafone’s mobile network issues. The product is released across Vodafone’s 60,000 4G sites in Italy and will soon be available to telco’s 5G and core networks. By 2022 the service is set to roll out to all European markets.

Google researchers have developed semiconductor chips created by AI

A team of Google researchers has created an AI model that designs next-gen chips faster than human designers. The model could build a design that optimises the placement of components on a chip within six hours. The team used a dataset of 10,000 chip layouts for an ML model and trained it using RL. The new AI-generated layouts were used in Google’s latest AI accelerator (TPU-v5). AI uses past experience to become better and faster.

Google Cloud launches new services to provide real-time insight

Google cloud launched three new ML-based services that will provide real-time data insights to users. The three services: Datastream allows users to replicate databases in real-time. Analytics hub lets users curate, create, and manage analytics exchanges securely and in real-time. Dataplex is a combination of Google cloud and open-source that allows users’ analyze their data at scale. A survey by Gartner found the average cost of poor data quality at $12.8mn per year.

Twitter starts initiative to analyze algorithm fairness on its platform

Twitter has launched an initiative on “responsible ML ” to reviews its algorithmic fairness with the aim to bring transparency on how it tackles “the potentially harmful effects of algorithmic decisions.” Concerns on algorithms used by internet platforms, which some allege promote violence, hate, racial/gender bias, is at an all-time high. Recently, controversies at Google’s AI ethics team resulted in the firing of two researchers and the resignation of a scientist.