11th Global Summit on Artificial Intelligence and Neural Networks

In recent years, biometric authentication has entered the mainstream; facial recognition on smartphones, technologies to speed up the airport experience, finger print access to online banking apps, or even biometric payment cards are just a few examples. While it may appear to be a novel notion, biometrics has been around for decades. Biometrics can be traced back to ancient times when fingerprints and handprints were used to sign and seal documents. The application of biometrics as a tool for identification and security purposes began in the late nineteenth century with the work of Alphonse Bertillon.  In 1879, a French police officer established an anthropometry method that involves measuring numerous physical traits such as height, weight, and the size of the head, arms, and feet to identify criminals. This approach was widely utilized by police agencies around the world and was regarded the gold standard for identification until the early twentieth century. In the early 20th c...

As artificial intelligence (AI) and machine learning (ML) gain traction in the cybersecurity business, fears about the future of cybersecurity jobs mount. Many people are concerned that AI will eventually replace human cybersecurity specialists; however this is not totally accurate and is based on many fallacies. One of the most common misconceptions about AI is that it can think and learn like a human, but in reality, AI is still constrained by the data on which it is educated. While AI is capable of analyzing enormous volumes of data and identifying patterns, it lacks human intuition, creativity, and decision-making abilities. Because threats and attacks can be complicated and subtle, cybersecurity requires a human touch. Cybersecurity specialists, unlike AI, can think outside the box, employ critical thinking abilities, and devise novel solutions. Furthermore, AI systems may be incapable of detecting novel and emerging risks. Furthermore, AI may be unable to recognize the context o...

  Ambient sensing is a type of sensing technology that collects information about one's surroundings. This data can be utilized for a variety of purposes, including analyzing the environment, informing users, and controlling devices. To put it another way, doesn't any sort of sensing technology qualify as 'ambient sensing'? The idea is to think about ambient sensing as a technology application rather than a specific sort of gear or software. Smart homes, for example, are outfitted with sound sensors that react to precise commands. This is not ambient sensing because it does not get insights from the surrounding general conditions. According to this conception, ' non-ambient ' sensing is 'direct sensing' — sensing that is calibrated to distinct, discrete inputs. The goal is to have a complete collection of contextual information from which to draw and interpret insights. The building is considered to have ambient intelligence when action is conducted aut...

AI Language Models Will Achieve Human Intelligence : According to futurist and engineer Ray Kurzweil, artificial intelligence will reach human-level capabilities by 2030. This will be decided when AI is capable of passing a legitimate Turing test. Collaboration between AI and humans will skyrocket across all professions: Artificial intelligence (AI) will be an essential component of day-to-day business operations by 2030, supporting individuals in their creative activities, generating new ideas, and tackling previously unsolvable problems. Collaboration with AI will be required in some circumstances. There are already good AI technologies used in creative professions, for example: VizCom generates rendered copies of sketches you supply it with. ArtBreeder generates AI-generated pictures from the photographs you supply it. WordTune rearranges and optimises the phrases you provide it. After you provide it enough speech data, Descript can duplicate your voice using text you offer it. In ...

It encourages independent learning and allows you to skip over subjects you've already mastered. Web-based learning is self-directed and facilitates individualized  learning. It promotes self-awareness and self-confidence while encouraging pupils to take charge of their own learning. Web-based learning is a method of learning that incorporates web-based technology or applications into the learning process. Web-based learning refers to learning materials given via a web browser, including content packed on CD-ROM or other media. Web-based education refers to all aspects and processes of education that make use of the World Wide Web as a communication medium and supporting technology. Web-based learning includes online education, virtual education, internet-based education, education through computer-mediated communication, tele learning, distance learning, cooperation, and so on. Web-based learning can be formal or casual. Teachers plan formal web-based learning activities. Informa...

AI is a big topic in many industries right now, but it's especially sensitive in music and the arts in general. Some people are anxious that they will lose their employment, while others are concerned that the value of human creativity will be eroded even further, and many are concerned that they will be left behind as technology once again renders entire business models outdated. Furthermore, things like this are happening that are only somewhat concerning. Creative AI could be the most disruptive technology for the music industry since the Napster piracy era. Already in 2023, independent researchers and big-tech businesses like Google and ByteDance have launched over ten different music AI models, allowing anyone to make custom tunes in seconds with only a text prompt. Hundreds of thousands of AI-generated songs are now available on streaming sites, thanks to off-the-shelf music AI technologies like Boomy. In general, generative AI tools for text and visual art, such as ChatGPT...