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AI is being used to train itself...and other news on the end of the world...

Okay, maybe not the end yet...

Although the prospect of machines teaching themselves how to do things sounds a bit concerning...I mean, what if they teach themselves to have autonomy, right?!?

The reality is, that so far, machines training machines isn't going well...

The idea is that training machines on their own generated content can exacerbate small biases in this generated content that, over time, can lead to potentially useless training data...

As one research put it, it's like an engine "choking on its own exhaust..." - Ross Anderson

But the idea is also in its infancy and techniques are being developed to improve the way in which machines teach machines...

Anyone tried experimenting with machine-on-machine training?

Things Get Strange When AI Starts Training Itself What happens if AI becomes even less intelligible?

Building your own LLMs doesn't mean you have to spend millions training from scratch...

Public LLMs like ChatGPT come with risk to enterprises as hackers focus their sights on these high visibility companies...

Private LLMs eliminate the risk to potentially exposing sensitive data and building them within an enterprise's firewall can still take advantage of open source foundational models (e.g. LLMs)...

Thus, enterprises require those who know how to fine tune these open source LLMs with company specific use-cases in mind...

Choosing between public and private LLMs Should your company leverage a public large language model such as ChatGPT or your own private LLM? Understand the differences.

Generative AI is only as good as the humans who use it…

And collaborations across humans are the seeds of innovation, GenAI or otherwise…

But collaboration is hard…

1. Bridging the Silos: Traditional organizational structures often create data and expertise silos, hindering information flow and stifling creative synergy. Imagine your marketing team using AI for personalized messaging, but lacking access to relevant customer data locked away in another department.
2. Building Trust and Openness: Embracing the unknown can be daunting. Implementing generative AI often generates fear and skepticism among teams worried about job displacement or biased outputs. Fostering trust through open communication, clear ethical guidelines, and human oversight is crucial for achieving buy-in and unleashing full potential.
3. Fostering a Culture of Experimentation: Innovation demands a mindset of fearless exploration. Creating safe spaces for learning from mistakes and celebrating failures is key to unlocking the true innovative potential of generative AI.
4. Measuring the Intangible: ROI for traditional technologies is easily quantified. However, the value of generative AI often lies in its less tangible impacts, like driving customer engagement, enhancing employee creativity, or inspiring new product ideas. Developing robust metrics that capture these qualitative benefits is essential for justifying investment and demonstrating success.

Let’s flip the script, and build a strategy that empowers…

• Break down the silos: Create cross-functional teams, empower data sharing, and encourage cross-pollination of expertise.
• Lead with transparency: Actively address concerns, demystify AI processes, and establish clear ethical frameworks.
• Celebrate the unknown: Encourage experimentation, reward failures as learning opportunities, and provide resources for continuous learning and skill development.
• Go beyond the numbers: Develop comprehensive metrics that capture the full impact of generative AI on innovation, customer experience, and employee engagement.

Imagine your design team partnering with the R&D department, using AI to generate and test innovative product concepts, leading to a groundbreaking invention that disrupts the market…

Remember, generative AI is not a solitary endeavor…

https://buff.ly/2MF48mq

What collaboration and innovation challenges have you faced with generative AI?

How Humans and AI Are Working Together in 1,500 Companies Examples of how they’re enhancing each other’s strengths.