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Insights from SXSW 2024: Reflections of a G-Research Software Engineer

Insights from SXSW 2024: Reflections of a G-Research Software Engineer

8 April 2024
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  • Technology

We work at the cutting-edge of our industry, which is why learning and development is a cornerstone of our employee experience. That’s also why we encourage our people to attend conferences and events, like South By Southwest. We want our people to hear from other experts within the industry, interrogate their research and think about how we can learn from their experiences.

Here, Michael W, an engineer in our Dallas engineering and infrastructure hub, provides an overview of what he took away from his time at SXSW 2024.

As a software engineer in G-Research's platform orchestration team, the opportunity to attend SXSW 2024 was one I jumped at. Unlike some industry conferences dominated by vendor pitches, SXSW stands out as a genuine marketplace of ideas, fostering insightful dialogue on emerging technologies.

Michael W Software Engineer

Navigating the AI Paradigm

Artificial intelligence was undoubtedly at the forefront of SXSW 2024, dominating the conference line-up. However, the narrative around AI was far from uniform.

The placement of generative AI on the Gartner hype cycle varied significantly across discussions. Depending on the session – and the organizations behind them – some argued that AI was still on the ascent, others saw today as the peak, while a few said we were already descending into the trough of disillusionment. There was a sea of noise surrounding AI, which made it difficult to extract actionable insights.

There was consensus on the biggest challenges in the generative AI space, namely around data quality, cost (both capital and talent), transparency, security, and bias. Human oversight emerged as an important control measure, but the prevailing tone was one of pessimism – most organizations will experience their AI challenges getting worse before they get better. Companies are struggling to derive actual value from generative AI, but are fearful of missing out.

One area of optimism stemmed from the productivity gains of AI, where the value of generative AI is already crystal clear among software developers. Bug fixes and features that previously took days can now be completed in a fraction of the time, and the velocity of LLM-assisted developers has been remarkably improved.

How do we build upon these improvements for individual developers? Numerous SXSW speakers suggested that the next frontier is leveraging generative AI to speed up entire engineering teams.

At G-Research, our journey into machine learning predates the current fervor. We have a robust track record in market forecasting, thanks to both the intellect of our people and our use of innovative AI and ML technologies.

Although we must navigate the challenges of generative AI like everyone else, we do so with experience and precision. Currently, we have teams exploring use cases to refine knowledge base discovery, streamline incident response, and further automate routine actions.

We have a clear vision of value, and are not getting lost in the allure of novelty. It is a privilege to contribute to an organization that approaches the AI landscape with focus and strategic intent.

Check out everything we got up to at SXSW via our social media.

LinkedIn

Keep an Eye on Hardware and Energy

Another frequent topic of discussion at SXSW was semiconductors, which are currently pushing the physical limits of chip manufacturing, supply chains, and capital allocation.

While the software layer of the AI stack is developing at breakneck speed, the hardware layer remains a bottleneck. These dynamics will require everyone to think more creatively about their hardware investments, while remaining strategically prepared for the advances that are sure to come. Keep an eye on emerging “specialty” hardware in the AI stack, like Groq’s Linear Processing Unit (LPU).

Quantum was also having its moment at SXSW, although with slightly less fanfare. Quantum hardware presents exciting opportunities in optimization, simulation, and security. There remain several practical challenges around operating temperature, cost, and the data architecture. However, there were several ambitious minds at SXSW that are working to reduce the barriers to commercial adoption.

Viability at scale for quantum may still be several years off, but organizations should start having early discussions around their readiness. Electronic trading in particular should stand to gain when that day comes.

Concurrently, the search for sustainable energy solutions to power these advancements is becoming increasingly critical. The focus on nuclear energy, grid optimization, and other power sources is not merely a technical challenge but a necessary investment for future scalability and sustainability.

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