Conexus AI

The Future of Work: It's Not What You Think Parents constantly ask me, "What skills should my kids learn to thrive in the future?" Programming used to be the go-to answer. But with AI automating routine coding tasks, many now see it as less secure. Liberal arts, once dismissed, are making a comeback because they're harder for AI to replace. And hands-on fields like cosmetology, immune to automation, are suddenly incredibly appealing. So, what's the answer? We want our kids to have fulfilling careers that express their unique talents and contribute value to the world. Traditionally, we've divided skills into "mind" and "hand" categories. But AI is rapidly automating many "mind" skills, making "hand" skills more valuable than ever. AI vs. Cosmetology: The New Career Choice It sounds crazy, but the choice between studying AI and cosmetology perfectly captures the career dilemma facing the next generation. AI represents the cutting-edge of technology, while cosmetology represents the timeless value of human connection and craftsmanship. Both are essential to the future of work. The Bottom Line The skills that will matter most in the future are those that AI can't replicate: creativity, critical thinking, emotional intelligence, and the ability to connect with others on a human level. This doesn't always mean working with one's hands but it can be a reasonable choice. These are the skills that will empower our kids to thrive in a world where AI is transforming every industry. More on this subject to come...

AI Regulation: Open Letter re CA SB1047 I am deeply concerned about the future of AI safety. Congress needs to take the lead on AI safety from CA's State Senate in light of their latest bill (SB1047). There is a more effective path forward. SB1047 attempts to regulate technology itself, rather than its applications, and lacks a clear technical foundation for achieving its safety goals. Said more plainly, the bill does not describe the technical means to achieve its aims, making it all but impossible to implement. This not only makes it difficult to implement but also risks stifling innovation in our state. I propose a different approach, one that aligns with the principles of accountability and innovation that California is known for. Let's hold AI developers liable for the errors in their deployed code, just as engineers are held responsible for the safety of their bridges and buildings. This approach empowers developers to define safety standards that are technically achievable and enforceable, ensuring compliance with existing laws. Legislators are ill-equipped to define ‘safety’; however, software developers are. They should say exactly what their systems are supposed to do. The ability to specify what a system should do, independently of how it does it, is in fact the cornerstone of modern engineering. This is why we don’t think twice about, for example, Boeing being liable for design flaws in its aircraft. Once this baseline of accountability is established, we can then have a more informed and productive conversation about additional regulations. With a clear understanding of the technical landscape, we can craft policies that promote both safety and progress. Neurosymbolic AI is already leading the way in this direction. The DoD already has a military-grade AI platform deployed, built on decades of research and proven in mission-critical applications, ensuring the safety and reliability of AI-generated code. We believe this approach is the key to unlocking the full potential of AI while safeguarding the public interest. I'm eager to continue engagement with legislators and the broader public exploring how we can work together to shape a future where AI is both powerful and safe.

It's #ModelMonday, and we're again diving into the world of digital twins. 🤓 The concept isn't new – Rosenblueth and Wiener explored it back in 1945! But what is new is the potential of neurosymbolic AI to create digital twins that go beyond basic simulations. Traditional digital twins often act like simplified scale models, capturing only the surface-level characteristics of their real-world counterparts. They might look the part, but they lack the depth and complexity to truly mimic behavior. Neurosymbolic AI changes the game. By combining symbolic reasoning with neural networks, we can build digital twins that understand the underlying logic and relationships within complex systems. This means they can predict outcomes, adapt to changes, and even reason like their real-world counterparts. Think of it as the difference between a toy car and a self-driving car. One is a static representation, while the other is a dynamic, intelligent system. The future of digital twins is here, and it's powered by neurosymbolic AI. #AI #DigitalTwin #NeurosymbolicAI

AI is reshaping industries, creating new opportunities, and transforming job roles. While some tasks may be automated, AI also opens avenues for upskilling, creativity, and innovation. Let's embrace the potential of AI to enhance productivity and drive meaningful change in the workforce! 💼 #AI #FutureOfWork #Innovation #Upskilling

In 1945, Rosenbluth and Wiener dropped a truth bomb about digital twins: "The best material model for a cat is another, or preferably the same cat." 2024 Translation: A true digital twin isn't just a simulation or a model. It's a living, breathing replica that mirrors the original in every way. Next time you hear about a "digital twin," ask yourself: Is it a mere shadow, or is it the real deal, like Rosenbluth and Wiener envisioned? A true model is possible, but only with neurosymbolic AI. #DigitalTwin #AI #DataScience https://lnkd.in/gF57xQ3f

OpenAI's CriticGPT: A good start, but why use a hallucinating LLM to check another? 🤔 Conexus AI's SQL Validator goes beyond AI critiques. We use math, facts, and declarative logic to rigorously validate your LLM-generated SQL code. Tired of endless testing, monitoring, and manual code reviews? Get 100% confidence in your SQL with Conexus AI. #SafeAI #SQLValidation #NoMoreHallucinations #TrustTheMath https://loom.ly/jd4HAiQ

Connecting databases is about more than just data transfer; it's about building trust in your AI-powered insights. 🔒 Conexus AI's Safe AI ensures your LLM-generated SQL code is accurate and reliable, so you can confidently make decisions based on your data. 🌐 #SafeAI #DataIntegration #TrustworthyAI

To regulate algorithms, including advanced AI, we can introduce circuit breakers. These would act as safety checks at various points to ensure systems don't link automations that we do not intend to link. While engineers, like myself, often strive to link automation into sequences and create evermore sophisticated systems, we need to balance this with outside views of the effects. With 30 million programmers worldwide, all aiming to meet quarterly goals through increased automation, it's essential to identify where we need to implement these safety measures to protect broader interests.

The Economist's article “Large language models are getting bigger and better” on April 17, 2024 on the challenges of scaling large language models (LLMs) rightly identifies the limitations of current AI architectures. While the relentless pursuit of larger LLMs suggests a future of limitless progress, a deeper dive reveals significant flaws. The "scaling hypothesis"—that more data and power equals human-like intelligence—misses crucial aspects. LLMs face serious hurdles: the dwindling supply of high-quality data, the inefficiency of scaling, and the simple fact that size doesn't equate to cognitive complexity. Here, neurosymbolic AI presents a promising alternative, blending the data-handling prowess of neural networks with the logical precision of symbolic AI. This combination not only promises enhanced efficiency and structured reasoning but also aligns closer with human cognitive processes. Neurosymbolic AI excels in areas where traditional models falter, offering a path to more sustainable, intelligent systems capable of real-world applications like airplane design and financial risk assessment. It’s time for the AI community to pivot towards technologies that not only scale but think smarter. https://loom.ly/96rDCD0

For increasingly complex environments, the ten year solution is a strategic pivot towards neurosymbolic AI. This approach marries the interpretability and rigidity of symbolic AI with the learning capabilities of neural networks. This Offers a pathway to manage complexity not by adding more of it, but by harnessing it effectively. Neurosymbolic AI can transform the way we develop and deploy data products, enabling rapid creation cycles that directly address core business challenges without the overhead of traditional models. It’s about cutting through the noise, focusing on the essentials, and delivering solutions that are not only effective but also understandable and manageable. There is an elegance of simplicity in this solution. The balanced approache of neurosymbolic AI brings clarity and efficiency, ultimately enhancing our ability to respond to change and uncertainty. #AI #NeurosymbolicAI #Technology #Innovation #Simplicity