The Artificial Intelligence Podcast | Podcast on Spotify
Open AI has sparked criticism by considering allowing users to create AI-generated pornography and other explicit content with its products. The company maintains that its ban on deepfakes will still apply to adult material, but is exploring the possibility of "responsibly" generating NSFW content, such as erotica and extreme gore. While Open AI clarifies that it has no intention of creating AI pornography and prioritizes the protection of children, concerns have been raised about potential exploitation and the company's ability to limit harmful material. The debate has prompted discussions about the ethical boundaries and responsibilities of companies in developing such technology.
Social Media Platform X Introduces AI Audience Feature
Social media platform X has introduced a new feature called "AI Audience" that enables advertisers to define target audiences using AI. Advertisers can input a brief description of their target audience, and X's AI system will generate a pool of relevant users within seconds. While some users praised the feature as a game changer, others expressed concerns about potential biases and stereotypes. The move aligns with X owner Elon Musk's proactive approach to integrating AI into the platform. Despite some skepticism, the overall response to the new feature has been positive, with users seeing it as a smart development for advertisers.
OpenAI's Chat GPT and the Rise of Artificial Intelligence
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.
Meta Platforms Expanding AI Offerings for Ads
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.
Using AI to Reduce Food Waste at Hungryroot
New York-based startup Hungryroot is using artificial intelligence (AI) to reduce food waste and provide a more personalized 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 minimize 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.
AI Model TRTpred for Predicting Tumor-Killing Immune Cells
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.
