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AWS executive Kanishka Agiwal, shared his thoughts on Machine Learning its applications, growing adoption in different sectors, function in the future, as well as AWS role in building and supporting the ML ecosystem.

Machine Learning (ML) is now powering a wide range of applications in organisations across various industries. ML is accelerating digital transformation and catalysing business processes, and Amazon Web Services (AWS) is one of the leading firms selling automatic ML methods and pre-trained models to businesses and developers. In an exclusive interview with The Hindu, Kanishka Agiwal, Head Service Lines, AISPL for AWS India & South Asia, shared his thoughts on ML its applications, growing adoption in different sectors, function in the future, as well as AWS role in building and supporting the ML ecosystem.

The following transcript has been edited for clarity and brevity.

Earlier, ML technology was limited to a few major tech companies and academic researchers. Things began to change when cloud computing entered the mainstream. Compute power and data became more available, and ML is now making an impact across every industry, be it finance, retail, fashion, real estate, and healthcare. It is moving from the periphery to now becoming a core part of every business and industry.

ML is already helping companies make better and faster decisions. When deployed with the right strategies, ML increases agility, streamlines processes, boosts revenue by creating new products and improving existing ones, and enables better, faster decision making. Theres no doubt ML and artificial intelligence (AI) can help companies achieve more.

As often happens in a crisis, companies tend to step back and think more strategically about their future operations. Weve seen healthcare organisations lean on technology and the cloud to get accurate, trusted information to patients and direct them to the appropriate level of care. Organisations of every size worldwide have been quick to apply their ML expertise in several areas, whether its scaling customer communications, understanding how COVID-19 spreads or speeding up research and treatment.

Several areas utilise ML including ML-enabled chatbots for contactless screening of COVID-19 symptoms and to answer queries. Using ML models to analyse large volumes of data to provide an early warning system for disease outbreaks and identify vulnerable populations. Making use of ML in medical imaging to recognise patterns and deriving contextual relationships between genes, diseases and drugs, and accelerating the discovery of drugs to help treat COVID-19.

I'm inspired and encouraged by the speed at which these organisations are applying ML to address COVID-19. At AWS, we have always believed in the potential of ML to help solve the biggest challenges in our world - and that promise is now coming to fruition as organisations respond to this crisis.

If you take some of the largest sectors such as agriculture, healthcare, citizen services, financial inclusion, youll notice ML at play. In agriculture, ML is playing a part in farm advisory, crop assaying, pest management, and traceability of crops.

Healthcare and life sciences organisations from the largest healthcare providers, payers, IT vendors, and niche ISVs across the globe are applying AWS ML services to improve patient outcomes and accelerate decision making. Some of the use cases we are seeing include using ML to accelerate the diagnosis of diseases, improve operational efficiency and delivery of care, population health analytics, and to aid scientific discovery. In India, Common Service Centres (CSC) are deploying ML to accelerate delivery of citizen services.

Increasingly, industrial customers across asset intensive industries such as manufacturing, energy, mining, and automotive are using ML to drive faster and better decisions to help improve operational efficiency, quality, and agility. ML services purpose-built for low latency requirements of industrial environments further remove barriers to industrial digital transformation.

Recently, we announced a collaboration with NITI Aayog to establish a Frontier Technologies Cloud Innovation Centre in India. This will bring together public sector stakeholders, startups, and academia to solve critical societal challenges.

Last year, Atal Innovation Mission, NITI Aayog, collaborated with NASSCOM to launch the ATL AI Step Up Module, with a focus on driving AI education among school students in India. Through AWS Educate, students will be able to gain hands-on practical experience on AWS ML services, including Amazon SageMaker.

In addition, the Indian Chamber of Food and Agriculture adopted AWS Educate to introduce certificate courses for agricultural engineering students. In March this year, we announced the AWS DeepRacer Womens League 2021 in India to help foster community learning, which aims to bring together women to gain hands on experience with ML.

To meet our customers where they are on their ML journey and help them achieve specific business outcomes, we provide the broadest set of ML and AI services for builders of all levels of expertise. AWS launched more than 250 new capabilities for ML and AI in 2020 alone.

We are building AI Services that allow developers to easily add intelligence to any application without needing ML skills. These services provide ready-made intelligence applications and workflows to personalise the customer experience, identify and triage anomalies in business metrics, image recognition, and automatically extract meaning from documents.

AWS has also launched end-to-end solutions, which dont require teams to stitch together multiple services themselves.

ML represents a unique opportunity for government and organisations to leverage public data for social good. From chatbots to supporting municipal services to contactless tracing of COVID-19, governments can harness ML to stay close to their citizens through deeper experiences. Organisations can better navigate and utilise data for more strategic and timely decisions if they are equipped with the appropriate technology capabilities. Leveraging ML can result in fewer errors and more timely decision making to enable organisations to execute initiatives with accuracy and speed.

Public safety can be improved over a range of possibilities, from ensuring safe roads, to preventing cyber-attacks and responding to natural disasters. ML will provide government organisations with the ability to improve safety across and beyond this spectrum. ML can dramatically streamline operational processes. As a result, it can save time, costs, and other resources so that organisations can focus on what is more important.

With ML, organisations can leverage data to develop and scale revolutionary ideas that result in cutting-edge research, far beyond human capabilities.

Link:
Machine Learning could solve biggest challenges in the world, AWS executive says - The Hindu

From voice assistants to self-driving cars, artificial intelligence and machine learning are overtaking every aspect of the industrial sector. Machine learning algorithms are used to automate laborious tasks in businesses to discover patterns in existing data without being explicitly programmed.

The field is continuously evolving and high-value predictions are being used to make better decisions in real-time without human interventions. Under recent circumstances, investments in machine learning companies have drastically increased. Analytics Insight presents the top machine learning funding and investments in Q2 2021.

Amount Raised: US$15M

Transaction Type: Not Specified

Key Investor(s): Bloomberg, Patrick Collison, and others

Lambda provides deep learning services to top tech companies like Apple, Microsoft, MIT, and others. It is an AI infrastructure providing computation to accelerate human progress.

Amount Raised: US$2M

Transaction Type: Not specified

Key Investor(s): Madrona Venture Group and Jazz Venture Partners

The companys SaaS platform leverages machine learning to discover, analyze, and improve clients business processes without interfering with users or requiring system integrations. Their solutions measure the problems faced by the clients and execute step-by-step processes to solve the issues.

Amount Raised: US$67M

Transaction Type: Series D

Key Investor(s): Chrysalis Investments

The company uses deep learning algorithms to provide cybersecurity services. Deep Instincts on-device solution protects against zero-day threats and APT attacks with unparallel accuracy. By applying deep learning technology, enterprises can gain unmatched protection against cyber threats.

Amount Raised: US$56M

Transaction Type: Series B

Key Investor(s): Tiger Global, Sequoia Capital, and others

Physna is a geometric deep-learning and 3D search company that focuses on comparing and analyzing 3D models. The company powers innovation in manufacturing by bridging the gap between physical objects and digital codes.

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Top Machine Learning Funding and Investments in Q2 2021 - Analytics Insight

University of the West of Scotland in Partnership with Raven Controls Limited

School of Computing, Engineering and Physical SciencesKTP Associate NLP & Machine Learning Research ScientistCompany Based - GlasgowREQ001219Salary up to 34,500 per annum plus 5,000 personal development budgetFull-time: 35 Hours per weekFixed Term: 30 months with potential for permanent employment

University of the West of Scotland (UWS) and Raven Controls are offering an exciting opportunity to a post graduate in Computer Science/Software Engineering/Information Technology or with a relevant degree involving a significant amount of software development to support Raven Controls. You will assist in the development of Raven Controls revolutionary event management. This involves inventing novel methods for NLP, data mining and data analysis using Artificial Intelligence and Machine Learning. You will work as part of the team to enhance the software to be used in the distributed environments. Since we are pioneers in the field, you will help us discover and apply innovative approaches to our existing technology. You should possess excellent communication and interpersonal skills, as well as the ability to work independently and as part of a high-performance team, collaborating with colleagues and sharing expertise. You will be able to demonstrate a proven interest in machine learning and NLP along with a sound knowledge of the C/C++/Python programming language.

The successful candidate will be offered the opportunity to register free of charge for a Higher Degree (Masters or Ph.D.), receive training in Chartered Management Institute (level 5), work with senior company management to realise benefits to the business and apply their degree and lead their own project in a business environment.

Raven Controls Limited was founded based of the MD's ten years experience of working in the Police force in Emergencies and Counter-Terrorism Planning and from his other business ID Resilience - which was formed to test and exercise clients' crisis management plans in a safe and secure environment. Incorporated in May 2017, Raven Controls Limited have developed a digital platform (web-optimised version of their Raven App) to provide real-time situational awareness for all stakeholders involved in event and venue management (particularly for crisis and incident management).

This allows users to stay in control and continuously informed through Raven's issue management system with integrated emergency management principles at its heart.

Find out more by visiting: https://ravencontrols.com/

Given the strategic important of the project, Raven Controls management have indicated their intention to retain the associate post-KTP subject to performance.

About KTP:This position forms part of the Knowledge Transfer Partnership (KTP) funded by Innovate UK. Its essential you understand how KTP works with business and the University, and the vital role you will play if you successfully secure a KTP Associate position. Please visit: http://www.uws.ac.uk/ktp for more information or contact Stuart Mckay at stuart.mckay@uws.ac.uk.

The University of the West of Scotland is committed to supporting your personal development and providing an inclusive working environment. UWS has an Athena SWAN bronze award, is a disability confident employer and welcomes other under-represented groups, as such we particularly encourage applications to support our diversity agenda.

Further information is available by contacting;Professor Naeem Ramzan: naeem.ramzan@uws.ac.uk ; 0141 848 3648 orMr Ian Kerr, Raven Controls: ian@ravencontrols.co.uk

Further information, including details of how to apply are available at https://jobs.uws.ac.uk/

Closing Date: Sunday 15th August 2021Interview Date: Week commencing Monday 30th August 2021

UWS is committed to equality and diversity and welcomes applications from underrepresented groups.

UWS is a Disability Confident employer.

University of the West of Scotland is a registered Scottish charity, no. SC002520.

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KTP Associate NLP & Machine Learning Research Scientist job with UNIVERSITY OF THE WEST OF SCOTLAND | 260243 - Times Higher Education (THE)