Efficient Methods for Natural Language Processing: Roy Schwartz is Professor of NLP at The Hebrew University of Jerusalem. We discuss an important survey paper (co-written by Roy) that presents a broad overview of existing methods to improve NLP efficiency through the lens of NLP pipelines. Building a premier industrial AI research and product group .. in three years: Hung Bui is the CEO of Vietnam-based, VinAI, explains the process of building a team that within a span of three years found itself listed among the Top 20 Global Companies in AI Research. Stanford researchers recently introduced tools to help users and developers understand large language models (LLM) in their totality. Given the central role of LLMs in NLP and in GenerativeAI, this suite of tools is an important step towards better transparency for language models.

With data science being such a broad and constantly developing field, it's really impossible to have all the knowledge in your head. Especially if some of this knowledge you use only occasionally. Also, if you're a beginner in a certain field, you'll have to refresh very often what you learned until it becomes actual knowledge at the crossroads of theory and practice. Having something that you could look at and get the info you need at a glance would be pretty helpful, right? That'something' is called a cheat sheet. And it has nothing to do with cheating.

Recent shifts in patient behaviors and preferences have intensified the demand for technology adoption throughout numerous healthcare processes. Artificial Intelligence is perfectly positioned to aid in many manual healthcare tasks, varying from diagnostics to AI patient billing. So, what exactly is AI? Artificial Intelligence is the wide-ranging branch of computer science engaged with building software programs that mimic human intelligence to perform tasks and make decisions. Automating redundant tasks is an effective strategy for reducing human labor and errors, which explains the recent momentum and growth of the AI industry. In fact, AI technology is predicted to reach $62 billion market value in 2022 alone, an increase of 21.3% from 2021.

YOLO (v7 and v5) both are state of art object detection algorithms. Both (YOLOv5 and YOLOv7) have been written in the PyTorch framework, while the latest among them is YOLOv7. Both are good, but each has its own limitations and drawbacks. I have received many messages on LinkedIn from people about the issues they are facing with using YOLOv5 and YOLOv7. In this article, I will answer the most frequent questions that I received, which can help you to understand and decide which algorithm is best according to your use case, and also why it's a challenge for people to decide which YOLO (v7 or v5) is better to be used in their products.

Artificial Intelligence is used widely. Virtually, all commercial industries have profited from AI advancements, but there is just as much (if not more!) hype surrounding AI as there is around data science. The phrases AI, Data Science, Machine Learning, Deep Learning, etc., are used almost synonymously of this, which further complicates things. Any technology where a computer program is attempting things that naturally occur to the human brain is referred to as artificial intelligence (AI). Every day, people demonstrate intelligence in actions, including reading written language, hearing speech, identifying items in pictures, and scheduling activities to make the most of their time.

Today this was been my first webinar in my career, so I wanna share my thoughts on #AutonomousVehicles #nvidia AI is the solution to self driving, Everything that will be autonomous The future is autonomous, and the possibilities are limitless. There are some gnarly waves in the topic, so what exactly an autonomous vehicle is and how does it work? Nowadays, AI is transforming the transportation industry without a human at the wheel. . Perception is the most important component of Autonomous vehicles. Mapping and adversal sceneries are the major components in AV.

Well, we all knew it was coming. Computers already easily overwhelm the best humans at chess and Go. Now they have done something far harder: achieved parity with David Brooks at writing. OpenAI's ChatGPT, released as a research beta two days ago, has done to the standard high-school essay what cameras did to photorealistic painting and pocket calculators did to basic arithmetic. It is open sign-up and free for now, but I suspect not for much longer, so go try it; and make sure to trawl social media for interesting and revealing examples being posted by people. As an open-world, real-ish (I'll define real-ish in a minute) domain, the correct standard for judging an AI on writing is not beating the "best" humans1 in a stylized closed-world competition (the existence of such competitions is a mark of a certain kind of simplicity), but achieving indistinguishability from mediocre humans. And when it comes to writing, nobody does mediocre more mediocrely than David Brooks.

It certainly feels like winter is here judging by the lack of sunlight. But a December like no other, as we have a World Cup to watch – although half empty, beer-less, air-conditioned stadiums in repressive Qatar does not sit well …Perhaps time for a breather, with a wrap up of data science developments in the last month. Following is the December edition of our Royal Statistical Society Data Science and AI Section newsletter. Hopefully some interesting topics and titbits to feed your data science curiosity. If you like these, do please send on to your friends- we are looking to build a strong community of data science practitioners.

A reader submits a report: Artificial Intelligence (AI) research company OpenAI on Wednesday announced ChatGPT, a prototype dialogue-based AI chatbot capable of understanding natural language and responding in natural language. It has since taken the internet by storm, with people marvelling at how intelligent the AI-powered bot sounds. Some even called it a replacement for Google, since it's capable of giving solutions to complex problems directly," almost like a personal know-all teacher. "We've trained a model called ChatGPT which interacts in a conversational way. The dialogue format makes it possible for ChatGPT to answer follow-up questions, admit its mistakes, challenge incorrect premises, and reject inappropriate requests," OpenAI wrote on its announcement page for ChatGPT. ChatGPT is based on GPT-3.5, a language model that uses deep learning to produce human-like text.

It's been said that you can't improve something that you can't measure. And so, in today's digital landscape, where every interaction becomes a measurable data point, data scientists are increasingly in high demand. The job of a data scientist now ranks sixth on U.S. News' "100 Best Jobs" list. And it's easy to see why. Data scientists solve real-world problems, which is why many data scientists (even entry-level ones) make more than a hundred thousand dollars a year.