Hey Everyone,
Wow, can you believe March is already here, bringing us to the end of Q1? I've just returned from an inspiring trip with Women in Data in London and at Vodafone. We dived deep into the world of AI in data visualization, discussed strategies for continuous learning, and explored ways to support more women in advancing their careers in data. Unfortunately, I fell ill upon my return, which has had me operating at half my usual pace. It's been a bit of a revelation for me, realizing how much of my happiness is linked to being productive—a challenging mindset I'm aiming to adjust. Despite this, I'm excited to share a bunch of great finds in this newsletter, focusing on the invaluable role of data and the latest developments in AI you might have missed last week.
Keep that curiosity alive and never stop learning,
Sadie
Have We Finally Found a Way to Quantify the Value of Data?
Have We Finally Found a Way to Quantify the Value of Data?
I vividly remember attending my first data conference over a decade ago, where the phrase "Data is the new oil" was heralded by presenters. As someone deeply immersed in the field and pursuing a master's degree at the time, I was thrilled. It felt like I had chosen the perfect career path. Yet, my experiences on the ground told a different story. Whether it was with marketing, product, or business teams, data often seemed to be an afterthought. When it was considered, it was typically used to bolster an argument or support a product launch. For years, those of us in the data sector have argued that data itself is both the product and the blueprint. However, adoption of this mindset was limited mostly to innovative startups, primarily because quantifying data's monetary value proved challenging, despite the frequent comparisons to oil.
Now, as the market sizzles, one thing has become clear with AI's rising popularity: data has quantifiable value. This is illustrated by deals like Reddit's $60 million agreement with Google to use its data for AI training. We're likely to see more of these transactions, especially in niche areas where unique data is scarce, as companies vie for a competitive edge.
So, does this mean we can now put a definitive price tag on data? Yes and no. The current market boom for data, fueled by the surge in generative AI, indicates a recognized value. However, not all data is created equal. This leads me to propose a model for valuing your data, centered around three key factors:
1. Exclusivity: Is your data unique?
2. Applicability: How can your data enhance AI training?
3. Volume: How much data do you have?
Having one of these factors is good; possessing all three is extraordinary. Although this model isn't flawless, it's a step forward. I'm eager to hear your thoughts on whether we've finally managed to assign a value to data and how you gauge this. Ultimately, I hope this conversation encourages more companies to integrate data design into their initial product strategies.
31 Days of AI, Day 1-15 Now Available
In case you missed it, days 7-15 are now available. During this time I covered everything from CPUs, Timeline of AI models, statistical models and neural networks.
Check out the videos here.
Last Week In AI
🥩 Klarna's CEO has made a bold statement about their AI, claiming it can replace the workload of 700 people in customer service. Dive deeper into this conversation here
👁️ Groq, an innovative startup focused on developing chips for generative AI, is introducing a groundbreaking technology called Language Processing Units (LPUs). These chips are revolutionizing the industry with their speed and capabilities. Additionally, Groq has expanded its horizons by acquiring Definitive Intelligence, a company known for its AI-driven business solutions, including chatbots, data analytics, and document builders. Find out more about this development here.
🚀 Elon Musk's lawsuit against OpenAI is turning heads, and it's a story worth following. This legal battle might shed light on the mysterious Q* and the debate around artificial general intelligence. Get the details here.
🧐 In an unexpected twist, researchers have discovered that AI chatbots show improved math skills when prompted with Star Trek scenarios. Yes, you read that right. Check out the study here
🇮🇳 Lastly, India is taking a cautious approach towards AI, recently demanding tech companies to obtain approval before releasing any "unreliable" AI tools. This move is sparking a significant conversation around the responsibility of AI development and deployment. Learn more about India's stance here.
Feel better soon! And great perspective on the value of data in the context of AI.