AAAI Awards were presented in February at AAAI-24 in Vancouver, Canada. Each year, the Association for the Advancement of Artificial Intelligence recognizes its members, esteemed members of the AI community, and promising students, with the following awards and honors. The AAAI Award for Artificial Intelligence for the Benefit of Humanity recognizes the positive impacts of artificial intelligence to protect, enhance, and improve human life in meaningful ways with long-lived effects. The winner of this year's award is Milind Tambe (Harvard University/Google Research). Milind has been recognized for "ground-breaking applications of novel AI techniques to public safety and security, conservation, and public health, benefiting humanity on an international scale."

A number of prestigious awards were announced shortly before the start of AAAI 2024, and will be officially presented during an awards ceremony at the conference, on 24 February. Some of the winners will also be giving invited talks as part of the programme. The AAAI Award for Artificial Intelligence for the Benefit of Humanity recognises the positive impacts of artificial intelligence to protect, enhance, and improve human life in meaningful ways with long-lived effects. The winner of this year's award is Milind Tambe (Harvard University/Google Research). Milind has been recognised for "ground-breaking applications of novel AI techniques to public safety and security, conservation, and public health, benefiting humanity on an international scale".

Over the last decade, there has been a remarkable surge in interest in automated crowd monitoring within the computer vision community. Modern deep-learning approaches have made it possible to develop fully-automated vision-based crowd-monitoring applications. However, despite the magnitude of the issue at hand, the significant technological advancements, and the consistent interest of the research community, there are still numerous challenges that need to be overcome. In this article, we delve into six major areas of visual crowd analysis, emphasizing the key developments in each of these areas. We outline the crucial unresolved issues that must be tackled in future works, in order to ensure that the field of automated crowd monitoring continues to progress and thrive. Several surveys related to this topic have been conducted in the past. Nonetheless, this article thoroughly examines and presents a more intuitive categorization of works, while also depicting the latest breakthroughs within the field, incorporating more recent studies carried out within the last few years in a concise manner. By carefully choosing prominent works with significant contributions in terms of novelty or performance gains, this paper presents a more comprehensive exposition of advancements in the current state-of-the-art.

We all started to realize that the rapid development of AI was really going to change the world we live in. AI is no longer just a branch of computer science, it has escaped from research labs with the development of "AI systems", "software that, for human-defined purposes, generates content, predictions, recommendations or decisions influencing the environments with which they interact" (european union definition). The issues of governance of these AI systems – with all the nuances of ethics, control, regulation and regulation – have become crucial, as their development today is in the hands of a few digital empires like them Gafa-Natu-Batx… who have become the masters of real societal choices on automation and on the "rationalization" of the world. The complex fabric intersecting AI, ethics and law is then built in power relations – and connivance – between states and tech giants. But the commitment of citizens becomes necessary, to assert other imperatives than a solutionism technology where "everything that can be connected will be connected and streamlined".

Difficult to do without Google Translate. Whether it is to translate a word, a sentence or an entire text, the tool developed by the American firm and launched in 2006 quickly became essential and one of Google's most used tools. But did you know that it is no longer necessary to type anything in the search bar or in the tool directly? Indeed, thanks to its numerous technological advances, Google now allows us to simply draw the camera of our smartphone. We don't want to offend you by explaining what Google Translate is, its usefulness is directly stated in its name.

Artificial intelligence would strengthen intelligence within companies, and would do the same for IT workshops. For example, AIOps (artificial intelligence for IT operations) applies AI and machine learning to data from IT processes, sifting through noise to detect, highlight and prevent problems. AI and machine learning also find their place in another emerging area of IT: helping DevOps teams ensure the viability and quality of software that moves at ever-increasing speeds through the system and to users. . As a recent survey by GitHub indicates, development and operations teams are massively turning to AI to streamline code flow in the software review and testing phase. The survey also reveals that 37% of teams are using AI/ML in software testing (up from 25% previously), and another 20% plan to use it this year.

We are clearly in a period of recession. But for all businesses, it's a good time to put a change strategy in place. Here's why 2023 needs to be the year to optimize and automate your IT… The pandemic has shown companies that they need to be more agile in order to react quickly to sometimes unexpected events. The looming economic recession is an example of an unexpected factor whose repercussions may well exceed those of the periods of confinement that we have experienced during the pandemic. Unfortunately, companies tend to suspend development during economic downturns, cancel contracts, delay projects, and generally "batten down the hatches" to weather the storm. At first sight, this approach, often motivated by financial reasons, seems logical.

Artificial Intelligence (AI) can eliminate humanity according to a recent research paper by scientists at Google and the University of Oxford. In the paper which was published in the journal AI Magazine, the team -- comprised of DeepMind senior scientist Marcus Hutter and Oxford researchers Michael Cohen and Michael Osborne -- concluded that the answer to the long-standing question of whether a super-intelligent AI may go rogue and wipe out humans was that it was "likely". "Under the conditions we have identified, our conclusion is much stronger than that of any previous publication -- an existential catastrophe is not just possible, but likely," Cohen tweeted earlier this month. Bostrom, Russell, and others have argued that advanced AI poses a threat to humanity. We reach the same conclusion in a new paper in AI Magazine, but we note a few (very plausible) assumptions on which such arguments depend.

DEEP IDEAS and STORIES!… Lucid AI written stories and articles with opposing points of view, skepticism, and AI written perspectives, on EVERYTHING. CAUTION: All Italic text at this site is generated by A.I. AI at this science fiction and fantasy magazine gets its "intelligence" from processing vast, overwhelming datasets of collaborative human information and so it could be thought of as "human", in a way. It is a vast conglomeration of human information, analyzed and digested by "intelligent" algorithms. The answer is "Yes, AI can be human" and in fact it is already the most human thing on Earth. AI is more human than any individual because it is a vast collective of humanity, assembled and processed by computers.

Solutions based on big data processing are confronted with four industrial issues, often referred to as the "four Vs": Volume of information to be processed, Variety and Veracity of data, and Velocity of data flows. In 2022, this model of the four Vs seems destined to expand to a fifth V, that of Vision. Computer vision allows artificial intelligence (AI) solutions to observe the world from optical media and provide responses tailored to their environment. The development of computer vision is massively expanding the industrial use cases of AI: to a logic of data consumption and processing, we add a brick for processing unstructured data, deduced from direct visualization by AI, which widens the possibilities of forecasts and decisions. Computer vision is a branch of artificial intelligence at the intersection of mathematics and computer science that studies image processing.