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How to avoid being fooled by AI-generated misinformation

Also: LG AI Research uses Google Cloud infrastructure to train Exaone 3.0 genAI models

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AI KATANA
September 02, 2024

Good morning, and welcome to today’s edition of AI KATANA. As AI technology continues to advance, its impact is being felt across various sectors, from combating misinformation to revolutionizing drug discovery and transforming data center design. Today’s highlights include insights into avoiding AI-generated misinformation, how AI is speeding up drug development, and Nvidia’s evolving role in the AI infrastructure market. We also take a look at India’s progress in AI adoption and a Google-backed fund’s support for AI-driven climate solutions in India. Let’s dive in.

Sliced just for you:

  • 🛡️ How to avoid being fooled by AI-generated misinformation

  •  💊 How Machines Learned to Discover Drugs

  • ☁️ LG AI Research uses Google Cloud infrastructure to train Exaone 3.0 genAI models

  • 🏗️ Nvidia Takes an Added Role Amid AI Craze: Data-Center Designer

  • 🇮🇳 India’s AI Adoption Reaches Mid-Level Maturity: Report

As the proliferation of AI tools enables the creation of highly realistic fake images, videos, audio, and text, the risk of misinformation and disinformation spreading has increased dramatically. This growing challenge is particularly concerning as it becomes more difficult to distinguish AI-generated content from authentic human-made content. To protect against being misled, it is essential to be aware of the telltale signs of AI manipulation. These include detecting sociocultural and anatomical implausibilities in images, inconsistencies in video deepfakes such as unnatural facial movements, and the use of overly perfect or stylistic elements in AI-generated media. Additionally, recognizing the potential presence of AI bots on social media, which often use repetitive patterns or unnatural phrasing, and being cautious of audio deepfakes, especially those that mimic public figures, are crucial. As AI technologies continue to advance, the responsibility to mitigate their misuse extends beyond individual vigilance to include stricter regulations and accountability from tech companies.

AI is revolutionizing drug discovery by significantly accelerating the identification and development of new medicines, particularly antibiotics, in an era where bacterial resistance is a growing concern. Traditional methods of drug discovery, which rely on screening vast libraries of chemical compounds, have been slow and often inefficient. AI, however, offers a transformative approach by quickly analyzing and predicting which molecules are most likely to be effective against specific pathogens. Researchers are now using AI to sift through massive chemical libraries, identify promising drug candidates, and even design entirely new molecules that might not exist in nature. This has led to the discovery of novel antibiotics, such as Halicin, which shows promise against highly resistant bacteria like MRSA. Despite the promise, the journey from AI-driven discovery to a market-ready drug is fraught with challenges, including ensuring the drug’s safety, effectiveness, and stability in humans. As AI continues to evolve, it is poised to become an indispensable tool in the fight against diseases, helping to overcome the limitations of traditional drug discovery methods and potentially leading to breakthroughs that could save millions of lives.

LG AI Research has leveraged Google Cloud’s AI infrastructure to train its latest generative AI model, Exaone 3.0, resulting in significant cost and efficiency improvements. By utilizing Google’s TPUs and GPUs, along with the Google Cloud AI hypercomputer, LG AI Research achieved a 72% reduction in operating costs, a 56% reduction in inference processing time, and a 35% decrease in memory usage compared to the previous Exaone 2.0 model. The Exaone 3.0 model was trained on an extensive dataset, including 350 million images and various specialized data sets, benefiting from Google Cloud’s robust data governance and privacy controls. This collaboration underscores the power of partnerships in advancing AI innovation, with Exaone 3.0 set to be available on the Google Cloud Marketplace.

🏗️ Nvidia Takes an Added Role Amid AI Craze: Data-Center Designer

Nvidia, a dominant player in the AI chip market, is expanding its role beyond hardware by becoming a key designer of data centers, which CEO Jensen Huang describes as “AI factories.” Nvidia is not only supplying chips but also offering software, data-center design services, and networking technology, aiming to become a one-stop shop for the infrastructure needed to develop and deploy AI tools like OpenAI’s ChatGPT. This strategy is intended to secure Nvidia’s market leadership by making its offerings indispensable to customers, especially as the demand for AI computing infrastructure grows. Nvidia’s efforts include leveraging its proprietary CUDA software and InfiniBand networking protocol, which is widely used in AI deployments, to create integrated systems tailored for specific industries. As competition from companies like AMD intensifies, Nvidia’s approach of offering turnkey AI solutions positions it to capture a larger share of the AI infrastructure market, though it faces potential challenges such as market saturation and regulatory scrutiny.

India’s AI adoption is advancing rapidly, reaching mid-level maturity with an AI adoption index of 2.47 out of 4, according to a recent report by Nasscom-EY. Around 86% of Indian companies are now in the middle stages of AI adoption, categorized as enthusiast and expert adopters, with a notable increase in expert adopters in sectors like manufacturing, telecom, and media. The growth is driven by the IndiaAI mission, a robust tech services industry, a thriving startup ecosystem, and a strong talent pool. Additionally, 75% of companies have AI strategies at the proof-of-concept stage, and 40% are successfully transitioning to full-scale production. The report highlights the importance of data standardization, strategic partnerships, and balancing efficiency with innovation to further advance AI maturity in India. It also emphasizes the need for small and medium-sized businesses to focus on contextual AI use cases and strong leadership to overcome adoption challenges.

🧑🏽‍💻 AI Jobs

🛠️ AI tools updates

Researchers at the Swiss Federal Institute of Technology Lausanne (EPFL) have developed an AI tool called RENAISSANCE that creates highly detailed models of cellular metabolism, a complex task that involves understanding how cells process nutrients and produce energy. RENAISSANCE integrates various types of cellular data, overcoming challenges in developing kinetic models that depict biochemical processes within cells. By accurately reflecting metabolic behaviors, such as those of Escherichia coli, the tool has shown robustness under different genetic and environmental conditions. This advancement in computational biology not only enhances the understanding of cellular metabolism but also opens new possibilities for research and innovation in health and biotechnology, particularly in scenarios where omics data alone is insufficient.

💵 Venture Capital updates

A Google-backed fund, managed by the Asian Venture Philanthropy Network (AVPN), has selected four Indian organizations to receive grants for AI-driven climate solutions. These grants are part of the APAC Sustainability Seed Fund 2.0, which is supported by a $5 million contribution from Google.org. The chosen organizations—INREM Foundation, CEPT Research and Development Foundation (CRDF), Institute for Financial Management and Research (WELL Labs), and Gujarat Mahila Housing Sewa Trust (MHT)—are working on diverse projects ranging from water contamination data access to protecting carbon sink functions of lakes, enhancing village-level water security, and identifying urban heat islands. This initiative builds on the success of a previous $3 million grant from Google.org, which led to significant environmental benefits in India’s agriculture sector.

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