https://demo.hume.ai – absolutely stunning demo of very responsive and emotionally adept voice chat.

A student reached out to me for a school project and asked me the following 5 questions: 1. What areas of research in AI deserve more attention? 2. Would it be possible to have AI in an educational setting as an omnipresent way of monitoring/grading students? 3. What would you say to someone with a pessimistic opinion about AI? 4. What are the main ethical considerations and challenges regarding the use of AI? 5. How do you think the relationship between machines and humans will be in the future? My answers are below. Feel free to reply with your own answers! ## What areas of research in AI deserve more attention? Building on the impressive capabilities of large language models (LLMs), an emerging trend in AI research is the development of agent-based AI systems. These systems enhance LLMs with additional capabilities, such as the ability to use tools, learn from interactions, and work autonomously on complex tasks. Examples of such systems include Devin, CrewAI, Autogen, and ChatDev, each designed to autonomously solve problems in various domains. Devin, developed by Cognition Labs, is an agent-based AI system focused on software engineering tasks. It can autonomously plan and execute complex development workflows, learn new technologies, find and fix bugs, and contribute to open-source projects. Similarly, CrewAI, Autogen, and ChatDev are autonomous agent-based frameworks that orchestrate teams of AI agents to collaborate on a wide range of tasks. The potential applications of agent-based AI are vast, extending to all sorts of complex, multi-step problems that could benefit from enhanced autonomous AI systems. However, while many research groups are working on developing these systems, there has been insufficient systematic study comparing the different approaches to each other. Typically, when a new agent-based system is announced, researchers compare its performance to unenhanced LLMs like GPT-4. However, this is not an apples-to-apples comparison, as the agent-based systems have additional capabilities beyond the base LLM. For example, Devin's performance on software engineering benchmarks was compared against raw LLMs, showing a significant advantage. This comparison is misleading, as it doesn't account for Devin's additional tools and capabilities.

My friend is a product manager at Deepgram, and they just released a ten times faster text-to-speech model as well as a very fast speech-to-text. This demo shows how combining it with Groq for fast LLMs, we can build a completely hands-free conversational experience https://www.youtube.com/watch?v=J2sbC8X5Pp8 the demo at their own website it also very impressive https://aura-tts-demo.deepgram.com/# (but does not use Groq yet, so a bit slower)

"This void of emotional connection is precisely what romantic chatbots—and the deep-learning algorithms that power them—are trading in. Nearly half of all men, 45%, are expected to use AI for romance, marking a significant increase from the previous year, according to a new report from McAfee Research. Ads for AI girlfriends abound on TikTok, Instagram and Facebook. Sadly, demand is high." Very thought-provoking article with deep and very sad insights into the topic. https://client.13d.com/share/65ebb8f1dfb64

"Perhaps it is better to focus on what AIs can’t do, and ask if this tells us something about consciousness. For instance, they have a lot of trouble maintaining a persona, acting as a cohesive agent in the world. I’ve found that I can always break out an AI out of some adopted persona by simply ordering it, yet again, to drop the act (even if it has previously been explicitly told to never under any circumstances do so). The philosopher David Chalmers calls this the problem of “unified agency” in his own examination of whether or not LLMs like Claude are conscious." I extensively use agency with OpenAI ChatGTP and its ability to maintaining a persona (of a game master, or a coach, or an interviewer) is the biggest differentiator on the market of LLMs right now. This way, the whole emerging concept of agent architecture depends on the ability to make the model behave as if it is more conscious. https://www.theintrinsicperspective.com/p/ai-keeps-getting-better-at-talking