Tamar Eilam: IBM’s AI Sustainability Leader on Green Computing & Women in Tech
As artificial intelligence reshapes industries, the need for sustainable computing has never been more urgent. At the forefront of this movement is Tamar Eilam, an IBM Fellow and Chief Scientist for Sustainable Computing, who has dedicated her 24-year career to reducing AI’s environmental footprint.
The Sustainability Challenge in AI
AI’s rapid growth comes with staggering energy demands. A recent Goldman Sachs report revealed that a single ChatGPT query consumes 10x more electricity than a Google search. With AI projected to increase data center power demand by 160%, Eilam’s work at IBM is critical to mitigating these impacts.
“There needs to be a focus on sustainability in general,” Eilam told TechCrunch. “We have an issue—and also an opportunity.”
The Energy Paradox
Eilam highlights a key industry dilemma: while AI itself is energy-intensive, it also holds the potential to decarbonize sectors like power grids. Renewable energy sources (solar, wind, hydro) are inconsistent, but AI can optimize grid operations by:
- Shifting workloads to align with energy availability
- Reducing computational waste through smarter algorithms
IBM’s Sustainable AI Initiatives
1. Kepler: Measuring AI’s Carbon Footprint
Eilam spearheads Kepler, an open-source tool that tracks energy consumption of containerized applications—a breakthrough for transparency in AI sustainability.
2. Chip-Level Sustainability
Beyond energy use, Eilam addresses hardware impacts:
- Collaborating with the National Science Foundation to identify toxic “forever chemicals” in AI chips
- Researching eco-friendly alternatives to traditional semiconductor materials
3. Efficient Model Training
IBM’s strategies to cut energy waste include:
- High-quality data curation to reduce training time
- Speculative decoding for faster inference
- Granite models in multiple sizes, allowing users to choose the most energy-efficient option
“We build observability into everything—energy use, latency, throughput,” Eilam explains. “Trust starts with transparency.”
Women in AI: Breaking Barriers
As a female leader in a male-dominated field, Eilam champions diversity:
- Co-led workshops on unconscious bias at IBM Research
- Advises women to “persist and voice opinions—repeatedly if necessary”
- Highlights how women often underestimate their qualifications compared to male peers
The Future of Ethical AI
Eilam calls for:
- Investor scrutiny of startups’ energy disclosures and data sources
- Stronger regulations with explainability at their core
- Industry-wide transparency to build trust in AI systems
“If we can’t explain AI’s decisions, we risk unintended consequences,” she warns.
This profile is part of TechCrunch’s ongoing series highlighting women shaping the AI revolution.
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