AI for customer experience, service, and suppor. One of the most common enterprise use cases for AI revolves around customer experience, service, and support. For example, chatbots use both machine learning algorithms and NLP to understand customer requests and respond appropriately. And they do it faster than human workers, and at a lower cost. AI also supports recommendation capabilities, which use customer data and predictive analytics to suggest products that customers are most likely to need or want and therefore buy.

The International Builders Show (IBS) 2024 has set a new precedent for the future of residential living with its emphasis on 'Plug and Play' smart homes, a trend spearheaded by Cox Communities. This innovation represents a significant pivot towards homes that are not only smart but also seamlessly integrated and ready for immediate use, marking a transformative moment in the housing market.

AI Chatbots are relatively old by tech standards, but the newest crop — led by OpenAI's ChatGPT and Google's Bard — are vastly more capable than their ancestors, not always for positive reasons. The recent explosion in AI development has already created concerns around misinformation, disinformation, plagiarism and machine-generated malware.

These curated papers would step up your machine-learning knowledge.

The world’s first generative AI-powered search engine is here, and it’s in love with you. Or it thinks you’re kind of like Hitler. Or it’s gaslighting you into thinking it’s still 2022, a more innocent time when generative AI seemed more like a cool party trick than a powerful technology about to be unleashed on a world that might not be ready for it.

The VII IEEE World Engineering Education Conference (EDUNINE2023) will be held as a hybrid conference (virtual and face-to-face) in Bogotá, Colombia, March 12-15, 2023. Through combined virtual and in-person workshops, plenary sessions, panel discussions, and parallel presentations by authors, the four-day conference aims to explore and focus on the key challenges of the conference theme and changing times.

Here we go again! For the sixth year running, we present Neural’s annual AI predictions. 2022 was an incredible year for the fields of machine learning and artificial intelligence. From the AI developer who tried to convince the world that one of Google’s chatbots had become sentient to the recent launch of OpenAI’s ChatGPT, it’s been 12 months of non-stop drama and action. And we have every reason to believe that next year will be both bigger and weirder.

From steam power and electricity to computers and the internet, technological advancements have always disrupted labor markets, pushing out some careers while creating others. Artificial intelligence remains something of a misnomer — the smartest computer systems still don’t actually know anything — but the technology has reached an inflection point where it’s poised to affect new classes of jobs: artists and knowledge workers.

Artificial intelligence (AI) systems, in general, are engineered systems that generate outputs such as content, forecasts, recommendations or decisions for a given set of human-defined objectives. AI covers a wide range of technologies that reflect different approaches to dealing with these complex problems. ML is a branch of AI that employs computational techniques to enable systems to learn from data or experiences. In other words, ML systems are developed through the optimisation of algorithms to fit to training data, or improve their performance based through maximizing a reward.