Data Science Talent | Newsletter Edition 2
A monthly publication bringing you valuable Insights from the world of enterprise Data Science and AI.
Editor's comments and essential articles
Is Gen AI ready for prime time in the enterprise yet?
After the initial Chat GPT breakthrough moment and the relentless pace of innovation that followed in 2023, it's been interesting to observe a much-needed realism appear from many in the Data and AI community.
Although LLMs might well be one of the most important inventions in recent human history, it could take several years for GenAI to prove real value in the complex environment of large enterprises.??
Below are two of my favourite articles that are must reads for anyone who wants to have a realistic view of AI and what it can achieve in the near term as we enter 2024:
This excellent piece lays out the current state of open source LLMs and use cases for open source LLMs. ?
2. Why Transformative AI Will Be Really Really Hard To Achieve - Gradient Article
This article is actually from June 2023, but its points are entirely valid 6 months on.? It summarises the main arguments for why the AI Revolution will take longer than most people imagine it will. Its a masterpiece from an excellent AI research publication based out of Stanford University.
Realism Is Good
It’s a good thing that realism is starting to set in.? Both business stakeholders and AI practitioners must now have real conversations about the amount of hard work and investment required to drive transformation with AI.? Without this there will be little transformation.
Enjoy the rest of our newsletter, Damien Deighan - Editor.
Issue 5 of our magazine, The Data Scientist, is available in digital and print, and you can go here to SUBSCRIBE FOR FREE.
The Path To Responsible AI - Data Science Conversations Podcast
In this episode, Dr. Julia Stoyanovich of NYU delves into the world of responsible AI, exploring the ethical, societal, and technological implications of AI systems. She underscores the importance of global regulations, human-centric decision-making, and the proactive management of biases and risks associated with AI deployment. Through her expert lens, Dr. Stoyanovich advocates for a future where AI is not only innovative but also equitable, transparent, and aligned with human values.
We discussed the following topics:
To listen to Julia's interview, please click on the link below:
领英推荐
Our Latest Articles:
1 - From Humans to Hybrids: Preparing Your Workforce to Thrive in the Future ?By Philipp M Diesinger.
?Here, Philip considers how the influence of ever-evolving AI and globalisation is prompting a shift from a human-centric to a hybrid workforce. How are workplaces best suited to collaborate with AI, and what benefits does such a collaboration offer over traditional teams??
Read the full article:
2 - Charting the Evolution of Talent in Data Science at the Event Horizon of AGI?By Lin Wang.??
In this post, Lin considers the rapid transformation of AI – and the impact this has on the role of the data scientist. How can the data scientist adapt to meet the new challenges of fast-evolving tech, and utilise the opportunities it offers? What new skills and personal qualities should the Data Scientist bring to the table??
Read the full article:
3 - Embracing Neurodiversity: My Journey with ADHD and How Generative AI Propelled My Career in Data Science.
In this post, Elle reflects on her ADHD diagnosis, the challenges it initially presented and the positive impact it had on her career. She explains how her understanding of ADHD empowered her to use AI in new ways, and ultimately as a vehicle for augmenting neurodiversity:
Read the full article:
Remember, Issue 6 of The Data Scientist will be out on the 2Oth February 2024. Be sure to subscribe and be the first to receive it.
See you next month!
Data Science Talent Editorial Team.