PodsByVishwaaz

Possibly a new breakthrough has been achieved in the domain of artificial intelligence. According to a new study, by a team of researchers from The Neuro (Montreal Neurological Institute-Hospital) and the Quebec Artificial Intelligence Institute, the artificial intelligence networks modelled on human brain connectivity are equipped to perform cognitive tasks efficiently and effectively.

We have often seen politicians busy staring at their phones or tablets even when an important debate or a discussion over a proposed law is underway. The issue is, of course, not confined to any specific country's political representatives. Interestingly, now there's a software that keeps a check on politicians with such behaviour.

Conversational agents are a dialogue system through NLP to respond to a given query in human language. It leverages advanced deep learning measures and natural language understanding to reach a point where conversational agents can transcend simple chatbot responses and make them more contextual. Conversational AI encompasses three main areas of artificial intelligence research — automatic speech recognition (ASR), natural language processing (NLP), and text-to-speech (TTS or speech synthesis). These dialogue systems are utilised to read from the input channel and then reply with the relevant response in graphics, speech, or haptic-assisted physical gestures via the output channel.  

It’s impossible to imagine the future of work and labor without taking into account India’s future as the world’s fifth-largest economy. With a population of 1.3 billion people, the country is already having difficulty hiring its large and rising workforce. According to Ernst & Young’s research, the Indian workforce grows by 17 million people per year, yet only 5.5 million jobs are produced.

In the digital world, we use the term ‘futuristic organization’ to represent companies that are making maximum use of technology. The dominance of artificial intelligence in the commercial space has brought up hope even to falling economies. Fortunately, organizations are adopting disruptive trends like machine learning and its applications to automate decision-making.

Nuclear physics may be one of machine learning's newest frontiers

Since the 1940s, physicists have tried, but no one has yet created an efficient nuclear fusion reaction. AI and machine learning (ML) have, across many industries and applications, proved themselves quite capable at detecting subtle patterns in data that humans can't recognize. So could neural nets and the GPUs that power them help in nuclear fusion? The challenge, and it's a big one, would be to accelerate the worldwide quest to tame instabilities in hot plasmas and ultimately provide a source of sustainable, and carbon-free power.

Thanks to artificial intelligence (AI) and machine learning (ML), robots are now able to do these complex tasks. The advancement of AI and ML is already taking over jobs that were until now reserved for professionals and people with expertise.

 Despite the massive amount of IoT data captured, organizations are falling short of their enterprise performance management goals because AI and ML aren’t scaling for the real-time challenges organizations face. If you solve the challenge of AI and ML workload scaling right from the start, IIoT and IoT platforms can deliver on the promise of improving operational performance.