Plus, researchers created a digital tongue so AI can taste.
According to a recent analysis, the increasing use of AI technology could result in a substantial rise in electricity consumption. By 2027, AI servers are projected to consume between 85 to 134 terawatt hours annually, an amount comparable to the electricity consumption of countries like Argentina, the Netherlands, and Sweden. While these projections are not alarming, the significant energy demands of AI highlight the need for sustainable energy solutions.
Advanced AI large language models, such as ChatGPT and Bard, have already achieved the most important aspects of Artificial General Intelligence (AGI). These models can perform various tasks, operate on different modalities, handle multiple languages, and engage in in-context learning. However, there are challenges in recognizing AGI due to skepticism about metrics, alternative AI theories, concerns about human exceptionalism, and economic implications. Frontier models demonstrate the capabilities of general intelligence but still require metrics improvements and addressing alternative theories’ limitations.
An Australian Photo Festival, Ballarat International Foto Biennale, has established a new category for images created with artificial intelligence, naming it ‘Prompted Peculiar.’ The festival aims to explore the ever-growing role of AI in art through a competition that recognizes and celebrates promptography as a bona fide medium. Promptography is defined as the creation of computer-generated images by artists who remain indoors, distinguishing it from traditional photography. The festival’s inaugural AI art award was granted to Swedish artist Annika Nordenskiöld, whose winning image, “Twin Sisters In Love,” was generated using AI prompts. Nordenskiöld’s work challenges the notion of realism and gives rise to discussions on the ethical implications of AI in the art world.
Google has launched a new advertising product called Demand Gen Campaigns, powered by AI, to create targeted video and image ads on YouTube and other Google platforms. This allows advertisers to extend their social strategies beyond traditional platforms like Facebook and Instagram. With creative tools and powerful AI, advertisers can tailor their ads for specific audience segments. Demand Gen Campaigns aim to capture user attention and interest as viewers shift their social media time toward video sites like YouTube. Early adopters have already seen significant improvements in click-through rates and lower costs compared to paid social campaigns. This aggressive move by Google to disrupt social advertising may prompt Meta and other advertising platforms to enhance their video ad offerings to remain competitive.
Penn State researchers have created an electronic tongue that mimics the human sense of taste. This innovation aims to incorporate emotional intelligence into AI systems, which often lack the psychological understanding of human decision-making. The electronic gustatory system can detect all five primary tastes and has potential applications in AI-driven diets and personalized restaurant offerings.
Utilizing AI, researchers have developed an innovative algorithm called “HistoAge” that predicts age at death and uncovers the secrets of brain aging and neurodegenerative disorders. This powerful tool analyzes digitized brain tissue sections and accurately forecasts age, identifies regions susceptible to age-related changes, and correlates with cognitive impairment and Alzheimer’s disease. HistoAge offers a transformative lens for understanding the aging brain and advancing research in cellular changes underlying degenerative diseases.
AI is being hailed as a promising tool to transform the drug discovery process, shortening the stages before clinical trials. It has the potential to save time and reduce costs by up to 50%. AI-intensive pharmaceutical companies have already seen success in reaching clinical trial stages within a decade or less. However, independent verification and publication of these findings are necessary. Challenges remain, such as overcoming generative AI’s limitations and the need for rigorous testing and validation of AI-generated drug candidates. Despite these challenges, AI shows immense potential in accelerating drug discovery.