The Artificial Intelligence Podcast

OpenAI's Chat GPT has played a significant role in popularizing the use of artificial intelligence (AI) among consumers. Machine learning, a subfield of AI, is being applied in real-world applications, with companies like Google and Microsoft leading the way in developing AI technologies and hiring machine learning engineers. Machine learning involves using algorithms and statistical models for computers to learn from patterns in data. It has applications in various industries, including finance, healthcare, entertainment, and publishing. Machine learning engineers are highly paid professionals, with an average salary of $165,685, and the highest-paying locations are Silicon Valley, New York, and Seattle. To become a machine learning engineer, a background in computer science, mathematics, or engineering is typically required, and there are various educational resources available for learning machine learning. The demand for machine learning engineers is expected to grow as AI advances and its applications become more widespread.

New York-based startup Hungryroot is using artificial intelligence (AI) to reduce food waste and provide a more personalised food delivery experience. Customers answer questions about their preferences, allergies, health goals and cooking habits, and the AI-powered technology recommends recipes and grocery items accordingly. Customers can review and make changes to their order before delivery, and Hungryroot can minimise its own waste by recommending items based on availability. These efforts have led to an impressive 80% reduction in food waste at Hungryroot's facilities, and the company has achieved profitability by efficiently spending and building a business that customers love. Hungryroot has raised $75m in investments to support its approach.

Researchers have developed an artificial intelligence (AI) model, called TRTpred, that can accurately predict tumor-killing immune cells. The AI model was trained using gene-expression profiles from 235 T cell receptors (TCRs) of patients with metastatic melanoma. The model was able to accurately identify tumor-reactive T cells with a 90% accuracy rate. The researchers further refined the selection process by applying algorithms to identify T cells with high binding strength to tumor antigens. The combination of TRTpred and the algorithmic filters, known as MixTRTpred, was validated in mice by identifying tumor-reactive T cells capable of eliminating tumors. The researchers believe this AI model has the potential to revolutionize cancer immunotherapies by offering personalized targeting of the most effective tumor-killing T cells.

Meta Platforms, the parent company of Facebook and Instagram, plans to expand its generative AI offerings for ads. These tools will enable advertisers to automatically create variations of images and add text on top of them. The company stated that the tool will initially be launched in a test form without watermarks. However, the company views watermarks as an important safety feature and is working on how labeling will work for ads. Meta's move to expand its AI offerings comes as it invests billions in building and supporting its AI models. Google has also announced a similar expansion of its AI ads tools.

The Biden administration is taking steps to protect advanced AI models from being exploited by China and Russia. These models have the ability to analyze large amounts of text and images, but there are concerns that U.S. adversaries could use them for cyber attacks or to create biological weapons. One of the main threats is the creation of deepfakes and the spread of misinformation. Companies like Open AI and Microsoft have developed AI-powered tools that can be used to create convincing deepfakes and other misleading content. Another concern is the potential use of AI models to create biological weapons, and the use of AI in cyber attacks. To address these threats, a bipartisan group of lawmakers has introduced a bill to impose export controls on AI models and give the Commerce Department more authority.

The adoption of generative artificial intelligence (genAI) is increasing, but there is a shortage of the high-performance chips, specifically high-bandwidth memory (HBM) chips, needed to support its growth. SK Hynix, a major HBM supplier, announced that its HBM products are fully booked through 2025 due to high demand, leading to increased prices. However, other manufacturers like Samsung and Micron are increasing production to meet the demand. TSMC, the exclusive supplier of HBM technology, is also increasing capacity to alleviate shortages. Chip manufacturers like Intel and AMD are introducing new processors for AI functions, and LLM creators are developing smaller models tailored for specific tasks. Efforts are being made to meet the growing demand for AI chips and enable widespread adoption of genAI.

Google has released its new Pixel 8a smartphone, offering generative AI features at a more affordable price of $499. The phone includes Google's Gemini generative AI chatbot, along with features like Magic Editor, Circle to Search, and Best Take. The Pixel 8a has a 6.1-inch display, Tensor G3 chip, 128GB of storage, and a 64-megapixel wide-angle camera. The Magic Editor allows users to remove or manipulate objects within photos, while Circle to Search enables searching for products seen in photos. Best Take captures a series of images for group photos and allows swapping faces if someone blinked. Google aims to boost device sales with these AI capabilities and has partnered with Samsung for similar features in the Galaxy S24 phones.

A recent survey conducted by Art & Science Group reveals that nearly all high school seniors who plan to attend college are familiar with and actively using generative artificial intelligence (AI) tools. The survey found that 19 out of 20 students are familiar with generative AI, and 69% have used these tools for schoolwork, including writing essays and completing assignments. Additionally, around 40% of students reported using AI for recreational purposes. While concerns about the consequences and ethical implications of AI persist, experts emphasize the need for a balanced approach in integrating AI into educational institutions and guiding students in responsible usage.