- Data Pragmatist
- Posts
- Environmental Costs of AI
In partnership with
Welcome to learning edition of the Data Pragmatist, your dose of all things data science and AI.
📖 Estimated Reading Time: 5 minutes. Missed our previous editions?
The fastest way to build AI apps
We’re excited to introduce Writer AI Studio, the fastest way to build AI apps, products, and features. Writer’s unique full-stack design makes it easy to prototype, deploy, and test AI apps – allowing developers to build with APIs, a drag-and-drop open-source Python framework, or a no-code builder, so you have flexibility to build the way you want.
Writer comes with a suite of top-ranking LLMs and has built-in RAG for easy integration with your data. Check it out if you’re looking to streamline how you build and integrate AI apps.
👀 AI bots now beat 100% of CAPTCHAs LINK
Research shows that image-recognition bots can now solve Google ReCAPTCHA v2 challenges with a 100 percent success rate, matching human-level performance.
ETH Zurich PhD student Andreas Plesner and colleagues reveal that these bots are capable of identifying objects in CAPTCHA grids, such as bicycles and traffic lights, with near-perfect accuracy.
Though Google has largely replaced reCAPTCHA v2 with an "invisible" reCAPTCHA v3, the older system is still widely used on millions of websites as a fallback.
🖐️ New robot arm can detach its hand to crawl and grab objects LINK
Researchers at EPFL in Switzerland created a robotic hand that can detach from its arm and crawl independently to grasp objects, extending the arm's reach.
The hand, designed with a genetic algorithm and MuJoCo simulator, features five articulated fingers and a magnetic connector for autonomous attachment and detachment.
Capable of bending in both directions, the hand can lift multiple items simultaneously and function even in tight spaces, unlike larger robots like Boston Dynamics' Spot.
🧠 Environmental Costs of AI
Attending the IEEE TechX event brought to light the critical balance between technological progress and its environmental impact. Shivam Shivam, a guest speaker, emphasized the urgent need to address these concerns, particularly with the rapid development of artificial intelligence (AI).
AI's Environmental Impact
Several statistics presented at the event highlight the environmental costs of AI. For instance, ChatGPT emits an estimated 8.4 tons of carbon dioxide annually, surpassing the carbon footprint of an average person. Additionally, training models like ChatGPT-3 and ChatGPT-4 consumed around 700,000 liters of water. Each interaction with AI also carries a hidden environmental cost; it’s estimated that every 20–25 questions asked of ChatGPT consume about 500 milliliters of water.
Tech giants like Microsoft further emphasize the scale of this issue. Their daily energy consumption is enough to power 100 African countries for a day, signaling the massive energy demands of the tech industry.
Additional Environmental Costs
The AI industry also contributes to e-waste generation and the extraction of rare earth minerals, which are essential for producing advanced hardware. Moreover, data centers require significant energy for both operation and cooling, adding to AI’s environmental footprint.
A Sustainable Path Forward
To mitigate these impacts, we must adopt more sustainable practices. Using smaller, more efficient language models (SLMs) instead of large language models (LLMs) can reduce energy and water consumption. Precise prompting can also limit unnecessary interactions with AI.
Moreover, investing in green technologies, renewable energy for data centers, and eco-friendly hardware development are critical steps. Circular economy principles should be promoted to reduce e-waste through recycling and reusing hardware components.
Conclusion: Progress with Responsibility
As we advance technologically, we must act responsibly to minimize environmental costs. Striking a balance between progress and sustainability will ensure that technological advancements benefit humanity without jeopardizing our planet’s future.
Top AI-Powered Legal Platforms
Uizard
Features: Instant wireframing, smart element recognition, code-free design handoff.
Limitations: Limited customization, occasional slowness, reliance on templates.
Pricing: Free, Pro: $12/month, Premium: $49/month.
Attention Insight
Features: Instant heatmaps, predictive engagement analysis, platform neutral.
Limitations: Confusing dashboard, slow loading, limited customization.
Pricing: Solo: €19/month, Teams: €399/month.
Khroma
Features: AI-powered color suggestions, adaptive color accessibility.
Limitations: Limited color options, clumsy interface, exporting hassles.
Pricing: Free (beta version).
Jasper
Features: Smart user flow analysis, instant heatmaps, feedback polls.
Limitations: Glitchy responsiveness, outdated templates, limited customization.
Pricing: Creator: $39/month, Teams: $99/month.
Adobe Firefly
Features: Easy prototyping, interactive components, smart design versioning.
Limitations: Limited customization, frequent glitches, confusing interface.
Pricing: Individual: $4.99/month, Business: $37.99/month.
If you are interested in contributing to the newsletter, respond to this email. We are looking for contributions from you — our readers to keep the community alive and going.