Unlocking AI Workload Optimization with Intel and Deloitte

In the latest episode of CXO Spice sponsored by Intel, I was delighted to host Shakir Rizvi, Senior Manager, Business Strategy and Intel Alliance leader at Deloitte.

Key Takeaways:

Shakir brought to light the escalating significance of AI adoption, spurred by Generation Y’s impact on consumer markets. He stressed the necessity for businesses to calibrate strategic initiatives with technological strengths. Deloitte and Intel’s joint study revealed that scaling AI adoption remains a challenge despite of 94% business leaders recognize the pivotal role of AI.  Shakir unpacked the top 3 AI adoption challenges and shared how the strategic alliance with Intel is directed at overcoming these barriers through software and hardware optimizations.

Challenges in AI Adoption:

Deloitte’s market research and client conversations have identified three major obstacles in AI adoption:

1. Infrastructure Decisions: 29% of enterprises face difficulties in choosing the appropriate infrastructure to effectively manage AI workloads.
2. Elevated Costs: 37% of leaders finding it challenging to demonstrate the business value of AI initiatives. The complexity of AI projects leads to high initial investments.
3. Sustainability: 38% Enterprises already on the AI journey encounter difficulties in sustaining the increasing expenses of AI solutions

Intel and Deloitte’s Joint Efforts:

In partnership with Intel Corporation, Deloitte has explored both hardware and software aspects to tackle client challenges. Their ‘fit-for-purpose’ AI hardware and software optimizations methodology is a strategic initiative aimed at assisting enterprises in achieving an optimal balance between cost, performance, and energy consumption, thereby enhancing the ROI of AI investments.

Considerations for AI Workload Management:

Enterprises evaluating hardware and software options for AI workloads must consider several dimensions, including performance needs, hardware and software capabilities, deployment choices, and cost optimization. Intel’s Xeon CPUs are continuously evolving to boost efficiency and performance. While GPUs and NPUs may provide superior performance for certain tasks, not all AI applications require such processing power. Intel’s partnerships with Hyperscalers offer a variety of hardware choices to optimize costs. Software optimization is also critical, with Intel offering specialized extensions and libraries like PyTorch, TensorFlow, and openVINO to improve performance. Internal studies have shown significant performance improvements, with some cases achieving over a 75% increase while reducing energy consumption.

Looking Forward:

As enterprises explore the limits of AI capabilities, collaboration with infrastructure teams is key to thoroughly assess hardware and software optimization possibilities. The most effective strategy will be determined by each organization’s unique business strategy, AI workloads, resources, and sustainability objectives.

The alliance between Deloitte and Intel is a profound commitment to spearheading the future of AI optimization.  As the technological landscape evolves, this strategic alliance stands as a paragon of innovation and guides businesses through the complexities of AI integration.

I look forward to the continued AI workload optimization that will stem from this synergy.

Watch the full interview for more insights: https://www.youtube.com/watch?v=BFlgjRieuWo&t=353s