Data & AI Report – Data Science Trends September 2024

October 9, 2024

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September trends in data science saw introductions into advanced search engines, internal developments & data protection from potential AI threats.

We’ve covered some exciting news from some big names.

Read on for more on all these exciting developments!

Vinted migrate to Vespa – how the online second hand shopping phenomenon is keeping up with the growth & complexity of data

After hitting the limits of their previous search engine, Vinted were on a mission to find a more scalable alternative.

Introducing Vespa: an open-source search engine & vector database. Vespa supports vector and keyword search and searches within structured data, all in one query. It also integrates machine learning which enables real-time AI insights from their data. It’s proven to handle thousands of queries per second, making it the top-runner for managing large & complex data.

Already used by others including Spotify & Yahoo and with continuous application improvements being delivered, will we continue to see increased use of Vespa?

Read more about Vinted’s migration here.

QueryGBT – allowing easier and faster data analysis for Uber

Uber’s data platform handles a huge 1.2 million interactive queries each month. The idea of QueryGBT is to better manage real-time data analytics & to query massive datasets. A combination of Presto (open-source SQL query engine) and Apache Hudi, which has the capabilities for handling upserts and managing large volumes of data in a cloud-based or distributed environment.

The system is part of Uber’s broader efforts to handle large-scale, real-time data streaming and querying – integral to its data-driven approach to decision-making. It’s said to minimise generating reliable queries from 10 minutes down to 3 which is a massive productivity gain for Uber.

Using advanced AI, QueryGPT fits smoothly into Uber’s data system, cutting query time and increasing accuracy to handle their complex data needs.

Read more about the advancements here.

Dropbox & Lakera Guard securing LLM’s

In a blog posted this September, Dropbox delved into how they’re using Lakera Guard to protect their LLM’s from potential security threats posed by AI.

Citing the importance of maintaining the trust of their millions of users to protect their content, Dropbox talk about how they chose Lakera Guard last year to protect user data & uphold the reliability and trustworthiness of their intelligent features, as outlined in their AI principles.

What were Dropbox looking for in their quest for protection? Their considerations concluded that it has to be deployable on their existing infrastructure, have low latency, strong confidence scores and scope for continuous improvement.

Dropbox have since invested in Lakera Guard, proving their strong belief in it’s abilities. Furthermore, they’ve also collaborated with the teams to develop improvements on the software itself. Working closely with Lakera, Dropbox have been able to help them meet their requirements whilst achieving their own security goals, too!

Read the full blog here.

Conclusion

In today’s fast-paced digital landscape, companies like Vinted, Uber and Dropbox are navigating many complexities. Vinted’s switch to Vespa demonstrates the importance of scalable search engines as companies grow. Uber’s QueryGBT highlights the need for faster and more accurate data analytics. Meanwhile, Dropbox’s partnership with Lakera Guard emphasises the need to secure AI systems to ensure data remains protected as AI technologies advance.

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