April 15, 2025

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AI Impact Explored: Energy Demand, Governance, and Applications

Recent developments in the field of artificial intelligence (AI) have sparked discussions about its environmental impact, applications, and governance. The carbon footprint of AI remains unknown due to secrecy and difficulty in measuring it, with experts highlighting the need to consider the source of power used to train and operate AI models. Meanwhile, the growing demand for AI is driving up energy demand, with data centers consuming large amounts of energy and water. Lawmakers are concerned about the strain on the grid and potential increases in power bills for residents. On the applications side, AI is being used in various industries, including food service, healthcare, and transportation, with companies like Donatos Pizza and Presto launching AI-powered ordering systems. Additionally, there is a growing focus on AI research, with institutions like the SUNY College of Environmental Science and Forestry receiving funding to establish AI research centers. The US government has also released guidance on federal AI use and procurement, aiming to accelerate innovation and strengthen public trust.

AI's Carbon Footprint Remains a Mystery

The carbon footprint of AI remains unknown due to secrecy and difficulty in measuring it. AI models consume massive amounts of energy and water during training and usage. Experts say that the environmental impact of AI depends on how power is generated, not just the amount of power used. AI itself has the potential to develop new approaches to reducing its climate impact. The new administration's focus on winning the AI race against China is sidelining environmental concerns.

Data Centers Drive Up Energy Demand

The growing demand for AI is leading to an increase in power-thirsty data centers. These centers consume large amounts of energy and water, and their development is causing concerns about the strain on the grid. Experts say that data centers are responsible for about 2% of the US energy demand, but this is expected to rise to 10% by 2027. States are exploring alternative energy sources to power these centers.

Lawmakers Fear AI Data Centers Will Raise Power Bills

State lawmakers are concerned that the growing number of data centers will drive up residents' power bills. Data centers require large amounts of energy, and their development is causing concerns about the strain on the grid. Some states are exploring ways to ensure that data centers do not result in increased rates for other electric customers. Lawmakers are also seeking to protect residential and commercial customers from higher utility bills.

Donatos Pizza Partners with Revmo AI

Donatos Pizza has selected Revmo AI as its preferred vendor for a new AI ordering system. The system will automate phone orders and is expected to enhance the customer experience and increase order conversions. Donatos Pizza anticipates that the technology will drive revenue across its locations nationwide. The company is rolling out the system to all 174 of its restaurants by May 2025.

Presto Launches Phone Ordering Business Unit

Presto has launched a phone ordering business unit, expanding its enterprise-grade suite of voice AI for quick-service restaurants. The company's executive team is attending the Restaurant Leadership Conference to discuss its unified voice AI vision. Presto remains focused on delivering the best enterprise-grade drive-thru voice AI product and will demonstrate its leading solution at the conference.

ESF Receives Funding for AI Department

The SUNY College of Environmental Science and Forestry has received state funding to develop and advance artificial intelligence research. The funding will be used to establish the Center for Artificial Intelligence, Society, and the Environment. The center will focus on promoting inclusive AI research, addressing ethical concerns, and advancing responsible data use.

AI Benchmarking Debates Reach Pokemon

Debates over AI benchmarking have reached the popular game Pokemon. A post on social media claimed that Google's Gemini model surpassed Anthropic's Claude model in the original Pokemon video game trilogy. However, the post failed to mention that Gemini had an advantage due to a custom minimap. The incident highlights the challenges of comparing AI models and the need for standardized benchmarks.

Stanford HAI Releases AI Index Report

Stanford HAI has released its 2025 Artificial Intelligence Index Report, which highlights the latest trends in AI. The report finds that AI is becoming more powerful, efficient, and accessible. AI performance has improved significantly in benchmarks such as MMMU, GPQA, and SWE-bench. The report also notes that AI is being increasingly integrated into everyday life, with applications in areas such as healthcare and transportation.

Conju's AI Receptionist Helps Small Businesses

Conju's AI receptionist is helping small businesses manage calls and boost sales. The AI-powered system texts back missed callers, qualifies them, and books them via SMS. The system is integrated with a digital platform and provides a unified web-based interface for users to access all communications. Conju's AI receptionist is designed to help small businesses avoid losing revenue from missed calls.

OpenAI Reduces Safety Testing Time

OpenAI has dramatically reduced its safety testing time for AI models from months to days. The change is meant to speed up the development process, but some staff are concerned that it may compromise safety. OpenAI's tests are not as thorough as they used to be, and the company is rushing to maintain a competitive edge. The reduction in safety testing time has raised concerns about the potential risks of AI models.

OpenText Customers Leverage AI and Cloud Solutions

OpenText customers are leveraging AI, cloud, and security solutions to drive transformation and success. The company's software and AI are being used to address critical challenges, automate processes, and enhance cybersecurity. OpenText's customers, including BMO and Catalent, are using the company's solutions to improve collaboration, compliance, and customer experiences.

White House Releases Guidance on Federal AI Use

The White House has released guidance on federal AI use and procurement, aiming to accelerate innovation and strengthen public trust. The guidance directs agencies to focus on three priorities: innovation, governance, and public trust. It also emphasizes the need for robust risk management, particularly for high-impact AI. The guidance replaces previous guidance and adds new policies, including a requirement to buy American and maximize the use of AI products developed in the US.

Sedona Great Decisions Discusses AI

The Sedona Great Decisions Group will discuss artificial intelligence and its impact on national security. The group will consider the interests of the US in national and global AI governance, risks posed to international security, and competing interests in global AI governance. The discussion will be led by Group Member Carla Williams and is open to the public.

Key Takeaways

The carbon footprint of AI remains unknown due to secrecy and difficulty in measuring it.
* The growing demand for AI is driving up energy demand, with data centers consuming large amounts of energy and water.
* Lawmakers are concerned about the strain on the grid and potential increases in power bills for residents.
* AI is being used in various industries, including food service, with companies like Donatos Pizza and Presto launching AI-powered ordering systems.
* The SUNY College of Environmental Science and Forestry has received funding to establish an AI research center.
* The US government has released guidance on federal AI use and procurement, aiming to accelerate innovation and strengthen public trust.
* OpenAI has reduced its safety testing time for AI models from months to days, raising concerns about potential risks.
* Stanford HAI has released its 2025 Artificial Intelligence Index Report, highlighting the latest trends in AI.
* AI is being increasingly integrated into everyday life, with applications in areas such as healthcare and transportation.
* The White House guidance on federal AI use emphasizes the need for robust risk management, particularly for high-impact AI.

Sources

AI Carbon Footprint Data Centers Energy Demand Environmental Impact Artificial Intelligence