The development of counterfeit AI is a real concern as it is often created by humans with their own implicit biases and limited perspectives. One of the primary concerns regarding large language model systems is their potential impact on the job market. Due to the impressive content they generate, these systems are now being referred to as "human-competitive intelligence," which could lead to workers being replaced by #LLM systems in a wide range of professions, including art, writing, programming, and finance. A recent study conducted by Open AI, Open Research, and the University of Pennsylvania explored this issue, comparing GPT-4 capabilities to job requirements. The study found that 20% of the U.S. workforce may have at least 50% of their tasks impacted by #GPT4, with higher-income jobs facing a greater impact.

This is the augmented reality sports fans have been waiting for! Put yourself in an NBA game!!! NBA Commissioner Adam Silver unveils streaming experience of the future via the NBA App - and you can be in it! Is this a glimpse of the NBA Metaverse?

Our future is largely shaped by technology, and it goes beyond just utilizing a smartphone or tablet. The tech world has had a tremendous impact on how we live even before we recognize how important the event is. Every organization in the world right now is counting on data for making the right business plans and decisions. It would have been hard to imagine the world if there was no data. Most electronic devices are using IoT for data collection, be it smart cars or wearable tech, and we are surrounded by them.

Entrepreneur Mousumi Kapoor checks many boxes. After spending nearly two decades in data and analytics roles at organisations in the US and India, Mousumi wants to check one more box -- AI for Good. 'AI for Good' is a large global movement fostered by the United Nations. It involves using Artificial Intelligence and other deeptech to solve the most urgent challenges facing humanity. Mousumi's startup Continual Engine is an extension of that vision.

Deeptech has become a buzzword in the Indian startup ecosystem. The emergence of technologies such as artificial intelligence (AI), machine learning (ML), automation blockchain and drones, among others, has opened up plethora of opportunities. While the full potential of these technologies are yet to be unlocked, companies are already witnessing efficiencies going up. "The journey that began with bringing businesses to the cloud, adapting to e-commerce and building mobile apps to bring a seamless experience came a full cycle in the last decade. The year 2020 and the following decade are going to be about making the interactions or transactions even more seamless, and in a way that replicates human behavior," said Aakrit Vaish, co-founder and CEO, Haptik, a start-up that offers AI-powered chatbots. Quoting NASSCOM data, many reports said about 18 per cent of 1,300 Indian start-ups launched in 2019 are leveraging deep-tech.

DeepTech companies combine cutting edge science and advanced engineering with the objective of making a profound impact on humanity. One of the sectors most impacted by DeepTech is AI for Drug Discovery. In the second article in our DeepTech Series, we will focus on AI for Drug Discovery and profile four top tier companies in this sector. Drugs are among the most effective ways to combat disease. Drugs are used to fight cancer, relieve pain, prevent cardiovascular disease, alleviate mental illness, cure infectious disease, and much more.

DeepTech, or deep technology, is an ambiguous term that is generally used to refer to AI, robotics, chip development, Virtual Reality, Augmented Reality and the Internet of Things combined. It is also described as a merger between science, creativity and entrepreneurship. DeepTech companies are founded on scientific discovery and innovative engineering as opposed to business models. This means they have the freedom to work towards positively affecting humanity without adhering to a specific strategy. Due to their complicated nature and perceived lack of business applications, DeepTech startups have found it difficult to gain funding.