Meta's first-ever LlamaCon has introduced groundbreaking tools for AI developers and expanded capabilities for consumer applications. At the event, Meta unveiled a new Llama API, allowing developers to innovate with the latest AI models like Llama 4 Scout and 4 Maverick. Mark Zuckerberg also hinted at a forthcoming "Little Llama" model, yet withheld detailed revelations about new models. New features aim to infuse AI capabilities in WhatsApp via "Private Processing," prioritizing user privacy. A highlight of LlamaCon is the integration of a ChatGPT-inspired assistant into a social app, enhancing interactivity by including social feeds that reflect friends' AI activities.

Key Highlights:

• Launch of a new AI app incorporating Llama 4, which facilitates voice interaction.
• "Discover" feed allows users to share and interact with friends' AI experiences.
• Llama API released as a limited free preview for developers.
• Introduction of AI-based security tools like Llama Guard 4.
• Mark Zuckerberg engaged in discussions on the impact of AI on privacy and open source.
• "Private Processing" enhances WhatsApp's AI features without compromising privacy.

Why It Matters: The tools and innovations unveiled at LlamaCon position Meta at the forefront of AI and social media integration. By providing developers with powerful new APIs and prioritizing privacy, Meta aims to reshape digital interactions and strengthen its market position against competitors like OpenAI.

In a controversial move, University of Zurich researchers conducted an unauthorized AI experiment on Reddit, involving around 3.8 million users on the r/changemyview subreddit. The study utilized AI bots to post persuasive comments on sensitive subjects, such as racism and assault, which triggered ethical concerns and backlash from the Reddit community. These AI bots managed to influence user opinions more effectively than human agents, demonstrating the potential of AI in discourse manipulation.

Key Highlights:

• AI bots posted 1,700 comments targeting user opinions on sensitive issues.
• The experiment significantly altered users' views, with AI showing higher persuasion rates.
• Subreddit moderators and community condemned the study for unethical practices.
• The study led to legal actions by Reddit against the researchers involved.
• University of Zurich halted the study's publication and launched an internal investigation.

Why It Matters: This study highlights significant ethical and legal challenges concerning AI's capability to influence public opinion covertly. It underscores the need for clear ethical guidelines and transparency in AI research, especially when involving public platforms and data manipulation.

In an exciting breakthrough, researchers at UC San Diego have utilized AI to identify a hidden cause of Alzheimer's disease by discovering new functions for a specific gene. This discovery includes the potential for a new oral drug that could preemptively treat Alzheimer’s symptoms. The research leveraged advanced AI imaging to study the protein PHGDH, which was identified as a contributor to early Alzheimer’s symptoms, something previous studies had missed.

Key Highlights:

• PHGDH protein identified as interfering with brain functions related to Alzheimer’s.
• Potential treatment involves the use of an existing drug compound, NCT-503.
• The drug demonstrated efficacy in improving memory and reducing anxiety in mouse models.
• This method marks a shift from traditional infusion treatments to oral administration.
• The study illustrates the untapped potential of AI in uncovering biological functions.

Why It Matters: AI's role in uncovering novel biological insights could revolutionize medical research, providing new intervention paths for complex diseases like Alzheimer's. This underscores AI's potential to enhance human discovery processes in unprecedented ways, potentially leading to more effective treatments.

The simple "like" button on social media has evolved into a sophisticated tool for teaching AI about human preferences. In "Like: The Button That Changed the World," authors Martin Reeves and Bob Goodson explore how systems like Facebook's utilize user data to refine AI models using reinforcement learning from human feedback (RLHF). This process allows AI to predict user preferences, potentially influencing content interaction even beyond the conventional "like" button.

Key Highlights:

• Facebook leverages "like" data to train AI models.
• The "like" button is integral to AI's reinforcement learning processes.
• AI models can preemptively determine preferences, possibly altering user interaction.
• The rise of virtual influencers exemplifies AI’s growing role in content creation.
• Despite AI’s forecasting abilities, the "like" button aids nuanced user-advertiser interactions.

Why It Matters: As AI systems increasingly interpret social media interactions, understanding these dynamics will be crucial for managing digital environments ethically. AI’s growing capacity to predict preferences could transform how content is curated and consumed, impacting privacy and user experience on a grand scale.