Now Next Later AI — Artificial Intelligence Strategy and Transformation NowNextLater.ai

Our books: https://www.nownextlater.ai/aibooks
Our Insights: https://www.nownextlater.ai/Insights/
Our AI Academy: https://www.nownextlater.ai/AIAcademy

01:16 Search
02:07 Conversational Aid
03:45 Summarization
03:55 Background Knowledge
05:22 Education
07:19 Coding
09:10 Brainstorming
09:26 Writing Aids
10:25 Fiction Writing
13:13 Defining Your Use Case

Hey there! It's Inês here. I work with businesses on generative AI.
Here's something I've observed:

- Some leaders are very enthusiastic, seeing huge potential for
productivity gains with AI .
- Others are cautious, concerned about issues like "the bots
hallucinate" and prefer to wait.

It's crucial to strike a balance.

I recently hosted a webinar where I discuss the real workings of these
AI models, what they can and can't do, and how best to approach them. Simple, but informed insights.

⁠ http://www.nownextlater.ai⁠

There are many variables to consider when defining our Generative AI strategy. Having a clear understanding of the use case/business problem is crucial. However, a good understanding of benchmarks and metrics helps business leaders connect with this new world and its potential.

So whether you are intending to: 


select a pretrained foundation LLM (like OpenAI's GPT-4) to connect via API to your project, 
select a base open-source LLM (like Meta's Llama 2) to train and customize, 
or looking to evaluate the performance of your LLM 



the available benchmarks are crucial and useful in this task. In this video we will explore a few examples.

Hey there!

It's Inês here. Over the past few weeks I've connected with hundreds of Australian business leaders keen to understand Generative AI's opportunities and risks.

Given the interest, I have put together a short briefing of the latest
AI news and developments in Australia. I hope you find it valuable.



http://www.nownextlater.ai

Hi there, Today I will share how Generative AI models like ChatGPT are transforming software development.

A McKinsey study found that generative AI tools can help developers complete certain programming tasks almost twice as fast. For example, documenting and commenting code took half the time with AI assistance. Writing new code from scratch was 46% faster. And optimizing existing code was 65% faster with the AI tools.

These are huge potential gains in productivity. However, the study found the boost was lower for more complex tasks or for junior developers. The AI tools helped senior developers tackle unfamiliar problems 25-30% faster though.

The tools also significantly improved the developer experience. Coders reported feeling happier, more fulfilled and “in flow” when using the AI assistants. This is because the tools automated repetitive tasks and provided helpful information quickly.

But the study also highlighted some risks and limitations of generative AI for coding. The AI tools sometimes made erroneous recommendations that developers had to double check and fix. The AI didn’t have insight into the organizational context and requirements needed to ensure high quality code. And the AI struggled with more intricate coding tasks that required a big picture view.

The opportunity here is for developers actively collaborate with the AI, provide the necessary prompts and context, and review the AI-generated code. Proper training and coaching is key to ensure safe and effective use of these powerful new tools.

Overall, AI has incredible potential to boost developer productivity, free up capacity, and improve the engineering experience. But engineering leaders need a thoughtful approach to realize the benefits while managing risks. This includes extensive developer training, expanding use cases beyond just code generation, planning for skill shifts, and implementing governance controls.

AI-powered coding is here, but thoughtful human guidance is still essential.

See you next time and Stay Human.


http://www.nownextlater.ai

In this session we present our Generative AI Transformation Playbook,
grounding the approach in research and balancing risk with opportunity.