#AI Joule

[navitsap]

SAP AI Joule: Revolutionizing the Future of Intelligent Automation

In the ever-evolving landscape of technology, SAP AI Joule emerges as a game-changer for businesses looking to harness the power of artificial intelligence and machine learning to optimize their operations. This innovative platform is designed to bridge the gap between traditional business processes and the cutting-edge advancements in AI, bringing automation, smart decision-making, and efficiency to the forefront of enterprise solutions.

In this article, we will delve deep into what SAP AI Joule is, how it functions, and why businesses should consider integrating it into their operations to stay ahead in an increasingly competitive market.

What is SAP AI Joule?

SAP AI Joule is an advanced AI-powered platform built to drive automation, streamline processes, and deliver insights across various aspects of business operations. By leveraging machine learning, natural language processing, and data analytics, SAP AI Joule enables organizations to make smarter decisions, improve customer experiences, and enhance overall productivity.

The platform is part of SAP’s broader vision to democratize AI by providing businesses of all sizes with tools that were previously reserved for large enterprises. SAP AI Joule is not only a tool but an intelligent assistant designed to continuously evolve based on data and insights.

How SAP AI Joule Works

SAP AI Joule is powered by cloud-based technologies, which allow it to seamlessly integrate with existing enterprise software systems. It harnesses machine learning algorithms to analyze vast amounts of data and automatically uncover patterns, trends, and correlations that may not be immediately visible.

The system learns over time, continuously improving its accuracy and efficiency. By doing so, it supports businesses in automating repetitive tasks, predicting future trends, and making data-driven decisions in real-time.

Machine Learning at the Core

One of the standout features of SAP AI Joule is its machine learning capabilities. The platform can analyze historical data, recognize patterns, and predict future outcomes, thereby reducing the need for human intervention. This makes it particularly valuable in areas such as:

Customer behavior prediction

Supply chain optimization

Financial forecasting

Employee performance analysis

By leveraging AI in these areas, businesses can operate with greater precision and accuracy, minimizing human error and improving outcomes.

Natural Language Processing (NLP)

Natural Language Processing (NLP) is another key element of SAP AI Joule. NLP enables the system to understand, interpret, and respond to human language, whether it’s in the form of emails, customer queries, or internal communications. This feature makes it particularly effective in enhancing customer support and chatbot capabilities.

Through NLP, SAP AI Joule can extract critical information from text data and offer insights or recommendations based on this information. This allows businesses to automate customer interactions and provide timely responses without human involvement.

Real-Time Analytics

In today’s fast-paced business world, real-time decision-making is more important than ever. SAP AI Joule’s real-time analytics capabilities allow businesses to access up-to-the-minute data and insights, empowering them to make decisions based on the most current information available. This is crucial in industries such as finance, healthcare, and retail, where timing can make all the difference.

Benefits of SAP AI Joule for Businesses

The benefits of integrating SAP AI Joule into a business’s operations are numerous and far-reaching. Here are some of the key advantages:

1. Enhanced Efficiency

By automating repetitive tasks, SAP AI Joule frees up valuable time for employees to focus on more strategic and creative endeavors. This not only improves productivity but also reduces operational costs, leading to higher profitability.

2. Improved Decision-Making

With its ability to analyze vast amounts of data and predict future trends, SAP AI Joule provides businesses with actionable insights that can be used to make informed decisions. These data-driven decisions help businesses stay ahead of the competition and adapt quickly to market changes.

3. Better Customer Experience

By leveraging machine learning and NLP, SAP AI Joule enhances customer service operations, making it possible to automate responses to customer queries and resolve issues faster. This results in improved customer satisfaction, loyalty, and retention.

4. Cost Savings

Implementing SAP AI Joule helps businesses cut costs by automating manual tasks and improving resource allocation. With more efficient processes, companies can reduce errors, minimize waste, and streamline operations, leading to significant savings in the long run.

5. Scalability

SAP AI Joule is a scalable solution that grows with your business. As your company expands, the platform can adapt to new processes, additional data, and increased demands without requiring significant changes or additional resources.

6. Competitive Advantage

Incorporating SAP AI Joule into your business operations gives you a competitive edge in the market. With its AI-powered insights, your business can make quicker, more informed decisions, while optimizing workflows and operations to stay ahead of the competition.

Key Features of SAP AI Joule

SAP AI Joule is packed with powerful features that make it a compelling choice for businesses looking to innovate and modernize their operations. Here are some of the standout features:

1. Automated Business Process Management

SAP AI Joule automates routine business processes, including data entry, reporting, and workflow management. This reduces the workload on employees and eliminates the chances of human error, improving overall operational efficiency.

2. Predictive Analytics

With its predictive analytics capabilities, SAP AI Joule can forecast future trends based on historical data. Whether you’re predicting customer demand, supply chain disruptions, or sales trends, this feature ensures your business is always prepared for what’s to come.

3. Customizable Dashboards

The platform offers customizable dashboards that provide an at-a-glance view of key business metrics. This allows decision-makers to monitor performance in real time and make adjustments as needed to achieve their objectives.

4. Seamless Integration with SAP Ecosystem

SAP AI Joule is designed to integrate effortlessly with other SAP solutions such as SAP S/4HANA and SAP Business Technology Platform. This ensures that businesses can leverage their existing SAP infrastructure while incorporating the power of AI and machine learning.

Use Cases of SAP AI Joule in Various Industries

SAP AI Joule’s versatility makes it applicable across a wide range of industries. Let’s explore how it can benefit specific sectors:

1. Retail

In the retail sector, SAP AI Joule helps businesses forecast inventory needs, predict customer preferences, and automate the supply chain. Retailers can also use the platform to enhance the customer experience through personalized marketing and dynamic pricing models.

2. Manufacturing

Manufacturers can use SAP AI Joule to predict machine failures, optimize production schedules, and improve overall equipment effectiveness (OEE). By integrating AI into their operations, manufacturers can improve quality control and minimize downtime.

3. Finance

In the financial industry, SAP AI Joule helps banks and financial institutions detect fraud, optimize trading strategies, and manage risk. It can also automate regulatory compliance processes, saving time and ensuring accuracy.

4. Healthcare

In healthcare, SAP AI Joule can analyze patient data to predict health trends, improve diagnoses, and optimize resource allocation. It can also help healthcare providers enhance patient care by automating administrative tasks and improving communication.

SAP AI Joule and the Future of Automation

As businesses continue to embrace digital transformation, the role of artificial intelligence and automation becomes more pronounced. SAP AI Joule is at the forefront of this revolution, enabling companies to automate processes, analyze data, and make smarter decisions faster.

Looking ahead, SAP AI Joule will likely evolve with even more sophisticated machine learning models, enhanced NLP capabilities, and deeper integrations with emerging technologies like 5G, IoT, and blockchain.

Challenges to Consider When Implementing SAP AI Joule

While the benefits of SAP AI Joule are clear, businesses should also be mindful of some challenges when implementing the platform. These may include:

Data quality and availability: For SAP AI Joule to function optimally, it requires high-quality, accurate data. Organizations need to ensure their data is clean, structured, and readily available.

Change management: Introducing AI-powered solutions may require a cultural shift within an organization. Employees must be trained to work alongside AI tools and adapt to new workflows.

Initial investment: Like any enterprise-level software, the initial cost of implementing SAP AI Joule can be significant. However, the long-term benefits often outweigh the upfront investment.

Conclusion

SAP AI Joule represents a monumental shift in the way businesses approach intelligent automation. With its powerful machine learning, natural language processing, and real-time analytics capabilities, it enables organizations to automate processes, enhance decision-making, and improve overall operational efficiency.

As businesses continue to adopt AI-driven solutions, SAP AI Joule offers an innovative, scalable platform that is equipped to meet the demands of today’s fast-paced business environment. By integrating this platform, companies can gain a competitive edge, reduce operational costs, and stay ahead of the curve in the age of digital transformation.

In conclusion, SAP AI Joule is not just a tool—it's a catalyst for change. With its ability to streamline processes and unlock new business insights, it’s no wonder why so many companies are turning to this intelligent automation platform for the future.

[neeraj82]

https://saxon.ai/blogs/when-sap-joule-meets-microsoft-copilot-whats-in-it-for-you/

[saptutorials]

Generative AI with SAP Joule: A Comprehensive Guide

In the ever-evolving landscape of business technology, SAP Joule emerges as a transformative force, promising to reshape the way businesses operate. This proprietary AI assistant, developed by SAP, is designed to be a virtual co-pilot, enhancing daily work experiences across various organizational sectors. In this blog post, we’ll delve into the essence of SAP Joule, exploring its capabilities,…

[tangocardiaca]

Meet Asuka. She is a student at very prestigious college. Very hard-working and focus on goal she will put herself to the limit in order to pass exams. Literally. After her last exam and two sleepless nights she passed out. She was rushed to hospital and placed on ER. The EKG leads, that are placed on her, read her heart rhythm Her heart beats very fast and irregulary. Suddenly she went into ventricular tachycardia. 180 beats per minute and no pulse. Doctors rush to save young woman. They perform CPR, chest compressions and breathing through ambu. AED pads are placed on her chest. "Charging to 100 joules. CLEAR!" Button is pushed and Asuka's chest jumps, but heart is still in VTach. "Charge to 200. CLEAR!" Another shock goes through her heart as her chest jumps once again. She came back to normal sinus rhythm, but she must be observed. AED will be prepared if she goes to cardiac arrest once again. This time AI credit goes to @nicklasmuller Thank you very much for suggesting an edit.

[abr]

La quantità di energia che arriva dal sole alla terra ogni ora è 430 quintiliardi di Joules (430 seguito da 18 zeri). Ogni. Ora. La quantità di energia emessa dall'umanità intera nello stesso tempo è 0,0002 quintiliardi di Joules. Dubito fortemente che questo 0,0000 qualcosa percento rispetto all'energia solare riesca a provocare qualche effetto significativo sul clima, prevalendo sulla prima.

ispirato da https://x.com/MarcoDabizzi/status/1793489302338654498

Non sono state generate emissioni di CO2 per diffondere questo legittimo dubbio (si parla di energia solare, rinnovabile).

Battute a parte, è troppo difficile per i gretini? Ok, traduciamo. E' come se foste in salotto assieme a Godzilla e King Kong e la mamma raccomandasse a voi di prestare attenzione ai movimenti che fate, per via della cristalleria.

[cauchesque]

i think i do an adequate job compensating for this, but when thinking about ai power usage it is from a standpoint of thinking that a future where server farms take up more space than cities and suck up 1e24 joules yearly would be awesome. vast deserts of black glass cooling surface radiating heat away into space

[recreationaldivorce]

Each time you search for something like “how many rocks should I eat” and Google’s AI “snapshot” tells you “at least one small rock per day,” you’re consuming approximately three watt-hours of electricity, according to Alex de Vries, the founder of Digiconomist, a research company exploring the unintended consequences of digital trends. That’s ten times the power consumption of a traditional Google search, and roughly equivalent to the amount of power used when talking for an hour on a home phone. (Remember those?) Collectively, De Vries calculates that adding AI-generated answers to all Google searches could easily consume as much electricity as the country of Ireland.

[ID: Bar chart by The Lever titled "Energy Used to Power Online Searches". The Y axis is Wh per request, numbered in intervals of 2 from 0 to 10. The bars are: (numbers are based on a conservative reading of the Y axis, which only has a resolution of 2)

Google search at less than 0.5

ChatGPT between 2 and 4

BLOOM at 4

AI-powered Google search (New State Research) between 6 and 8

AI-powered Google search (SemiAnalysis) between 8 and 10

In the bottom-right it credits the source as Alex De Vries (Joule) and credits the chart to @/LeverNews

/End ID]

the title seems a bit silly; i think the environmental impact of ai is like as well known as the environmental impact of crypto, but in any case the stats still stand.

[wheat-singularity]

Article from a post I lost somewhere. Bottom line: training AI is expensive in terms of electricity cost, using it is less so.

All of these numbers are estimations:

Training GPT-3 used just under 1300MWh. That is about as much electricity as 130 average US homes used in a year, or 1.6 million hours of streaming netflix.

Classifying 1000 written samples used about 0.002kWh, equivalent to nine seconds of streaming netflix.

Generating text 1000 times took 0.047kWh, or 3.5 minutes of netflix.

Generating 1000 images used 2.907kWh, equivalent to 3.5 hours of streaming netflix (my calculation)

"de Vries calculates that by 2027 the AI sector could consume between 85 to 134 terawatt hours each year." Roughly the annual energy demand of the Netherlands.

(I don't know why netflix was the metric they went with but I guess it works)

[sucuretcannelle]

Game au shit

How Nash would introduce the characters in the selection menu

Aibreanne: "Daddy's girl" "She's hot, literally" "I wish I was a fireman" "Bambi"

Char: "Mini Jason" "Guns N' Roses" "Pico"

Jason: "Jason Voorhees" "Helloooo nurse!"

Kam: "Siran's dog" "Morticia"

Siran: "He makes me wanna eat an apple a day" "Stingy ass doctor"

Kazye: "Why him?" "Sergeant sleep" "Danny Phantom"

Joule: "Love this girl!" "Albert Einstein" "Do sexy scientist costumes exist? Just wondering"

Nash: "Oh shit it's me" " "He's single!" "Sexiest dude to roam Hell"

Aquinas: "Pac-Man" "One greedy motherfucker"

Raivath: "Do NOT piss this guy off" "Too many hands" "Little ladybug"

Azrael: "Outta sight, outta mind" "More angelic than most angels"

Orion: "Look what you've done" "What a lame weapon" "Ain't killin people with a toothpick"

Atlas: "I'm a motherfuckin starboy" "Grumpy pants" "Do not be afraid"

Duke: "Nice hat!" "He skipped horseback riding for this?" "Johnny Bravo"

Laura: "Cowgirl...yeah, both meanings there"

Adrienne: "That dude on the Monopoly box" "Chloe Bourgeois" "Veruca"

Salem: "According to my calculations, he'll lose this fight"

Aquinas: "Ursula" "What a snake"

Sanitive: "What's she gonna do? Chew some clothes off?" "Discord" "Shorty"

Alexi: "Bird boy" "Goddamn he makes me feel like an idiot" "Bre's plaything" "He's gotta be AI-generated"

Theros: "Sol? No..." "Why does Bre like this guy?" "What can he spell?

Vortex: "Raivath? NO? FUCK." "Do you have to sign a waiver before this fight?" "This fight's gonna start and we're gonna hear 50 bones crack"

Pippin: "I just know he's gonna do some dumb shit" "He's just as crazy as his dad"

Prompt: "What a weirdo" "Cavern Dweller"

*The rest probably just have their name tbh

[psychedelic-toads]

“de Vries calculates that by 2027 the AI sector could consume between 85 to 134 terawatt hours each year. That’s about the same as the annual energy demand of de Vries’ home country, the Netherlands.”

[talenteam]

Upscaling HR Operations with SAP SuccessFactors AI Capabilities

Artificial intelligence is no longer just a trend in HR; it's essential. From hiring to employee development, AI is making HR processes faster and smarter. SAP SuccessFactors is leading the way with AI tools that are improving how HR teams work and how employees experience HR services.

What was the evolution of AI for HR like?

AI has come a long way from being a buzzword to becoming an integral part of business operations across various sectors. AI for HR is no longer a futuristic concept; it’s a practical tool that provides deeper insights, automates repetitive tasks, and enhances decision-making processes. The impact of AI for HR functions is profound, influencing everything from how employees interact with HR systems to how organisations utilise data to drive business outcomes.

The 3 R’s:

SAP’s AI for HR Strategy

SAP’s approach to integrating AI into its products, particularly SAP SuccessFactors, revolves around three core pillars: relevance, reliability, and responsibility.

Relevance: SAP ensures that its AI functionalities are continuously updated to meet current business needs. This relevance is critical in maintaining the effectiveness of AI tools as business environments and technologies evolve.

Reliability: The AI features in SAP products are designed to provide accurate insights and results. Reliability is achieved through rigorous testing and validation, ensuring that the AI tools can be trusted to deliver meaningful outcomes based on the data within the SAP ecosystem.

Responsibility: SAP is committed to ethical AI usage. The company has established an AI ethics policy team to oversee the development and deployment of AI functionalities, ensuring they adhere to data privacy regulations and ethical standards. This commitment to responsible AI usage is essential in building trust with customers and end-users.

What are the AI Capabilities in SAP SuccessFactors?

SAP SuccessFactors integrates AI across its suite of HR solutions, offering both basic and premium AI functionalities that cater to different organisational needs.

Basic AI Features

The basic AI features embedded within SAP SuccessFactors are designed to enhance core HR processes without requiring additional licences or subscriptions. Some of the key functionalities include:

Learning Recommendations:

AI-driven personalised learning recommendations are based on an employee’s skills, completed courses, and organisational needs. This feature uses the Talent Intelligence Hub and a skills framework to suggest relevant learning opportunities, helping employees grow and develop in their roles.

Career Path and Skill Recommendations:

SAP SuccessFactors provides AI-generated career path suggestions and skill development recommendations, helping employees chart their career progression within the organisation. These recommendations are tailored to individual employees based on their current roles, skills, and career aspirations.

Enhanced User Experience:

AI in SAP SuccessFactors enhances the overall user experience by providing intuitive navigation and interaction within the platform. For instance, the AI-driven search functionality allows users to quickly find relevant information or perform specific tasks, reducing the need for extensive manual navigation.

Premium AI Features

For organisations looking to understand and put to use the advanced AI capabilities, SAP generative AI offers premium features that require additional AI unit licences. These premium functionalities include:

Joule Assistant:

Joule is an AI-powered assistant integrated into SAP SuccessFactors that supports various HR tasks. It offers conversational, navigational, and transactional support, making it easier for users to interact with the system. For example, Joule can help users write goal comments, request feedback, or generate job descriptions. While Joule is available as a built-in feature, certain advanced capabilities may require additional setup and integration.

Interview Question Generation:

This premium AI feature integrates with Microsoft Teams to generate interview questions based on job descriptions and required skills. It’s particularly useful for organisations that need to streamline their recruitment processes and ensure consistency in their interview practices.

Assistive Writing for Performance Management:

AI-driven assistive writing tools help managers and employees craft better performance goals, feedback, and other textual content. These tools ensure that written communications are clear, effective, and aligned with organisational standards.

What is the Implementation technique for AI in SAP SuccessFactors?

Implementing AI features in SAP SuccessFactors requires careful planning and consideration. Here are some key points to keep in mind:

Licensing and Procurement:

While basic AI features are included with SAP SuccessFactors, premium AI functionalities require the purchase of SAP generative AI unit licences. These licences are not limited to one specific product area; they can be used across various SAP applications, including SAP SuccessFactors, Fieldglass, and Ariba. Organisations need to work closely with their Customer Success Manager (CSM) to understand the licensing requirements and ensure they have the necessary units to access the desired features.

System Integration:

For AI features like Joule and interview question generation, organisations may need to integrate additional systems, such as Microsoft 365, to fully utilise these capabilities. Ensuring that all necessary systems are in place and properly configured is crucial for the successful deployment of AI functionalities.

Data Privacy and Compliance:

 With AI tools processing sensitive employee data, it’s essential to adhere to data privacy regulations. SAP’s commitment to responsible AI usage includes strict compliance with data privacy laws, but organisations must also ensure their internal processes align with these standards.

The Future of AI in SAP SuccessFactors

SAP is continuously evolving its AI offerings, with a strong focus on expanding the capabilities and reach of AI within SAP SuccessFactors and across its entire product portfolio. The roadmap for AI in SAP SuccessFactors includes plans to enhance existing features and introduce new functionalities that will further empower HR operations and improve the user experience.

For instance, while Joule currently supports only text-based interactions, future updates may include voice-based interactions and expanded language support. Additionally, SAP is exploring ways to make Joule and other AI features available on mobile platforms, further increasing accessibility for users.

Concluding Thoughts

The integration of AI for HR operations is transforming how organisations manage their most valuable asset: their people. SAP SuccessFactors is leading this transformation by offering a range of AI capabilities that enhance user experience, improve decision-making, and streamline HR processes. Whether through basic features like personalised learning recommendations or advanced tools like the Joule assistant, AI is helping organisations create more efficient, effective, and engaging HR environments.

TalenTeam's commitment to personalised support ensures smooth implementation and ongoing success. With a focus on efficiency and cost-effectiveness, we deliver results that exceed expectations, valuing clients' time and investment.

As AI technology continues to advance, organisations that embrace these innovative solutions will gain a competitive edge. By using the combined power of SAP SuccessFactors and TalenTeam, organisations can create great HR functions that anticipate future challenges, drive organisational success, and create a high-performance culture. Outpace your competitors with AI for HR. Optimise talent, build top teams, and increase employee satisfaction with SAP SuccessFactors and TalenTeam.

Contact us for a consultation. 

[hongjuelectronics]

High-Current Fuse Holder Thermal Management Technology: Ensuring Reliability in Industrial High-Load Environments

Introduction

In industrial equipment and heavy machinery, fuse holders are vital components of electrical protection systems. Under high-current conditions, fuse holders are prone to overheating, which can degrade performance or create safety hazards. To ensure reliable long-term operation in high-load industrial environments, advanced thermal management techniques are essential. This article explores the causes of overheating, effective thermal design strategies, material selection, real-world examples, and future trends.

1. Overheating Challenges in High-Load Industrial Environments

High-current fuse holders face the following overheating challenges:

Joule Heating: Electrical resistance generates heat as current passes through conductors. Higher currents produce more heat.

Contact Resistance: Poor contact at connection points increases resistance, generating additional heat.

Environmental Factors: High ambient temperatures or enclosed spaces hinder heat dissipation.

Design Flaws: Inadequate thermal pathways or improper venting lead to heat buildup.

Overheating can cause material degradation, reduce electrical performance, and increase the risk of failure.

2. Thermal Management Techniques for High-Current Fuse Holders

1. Optimizing Heat Dissipation Pathways

Effective thermal pathways are critical. Strategies include:

Enhanced Conduction: Using multilayer conductors to distribute heat. For instance, industrial fuse holders with integrated copper heat conductors efficiently transfer heat to the exterior.

Ventilation Design: Adding vents or air channels to improve airflow.

Thermal Bridges: Placing thermal bridges to direct heat to cooling components.

2. High-Thermal-Conductivity Materials

Materials significantly impact thermal performance:

Metal Conductors: Use of copper and aluminum alloys, with silver plating for lower resistance.

Thermally Conductive Polymers: Incorporating fillers such as boron nitride to improve thermal conductivity in insulating materials.

Thermal Coatings: Applying heat-dissipating coatings on external surfaces.

3. Innovative Structural Designs

Various structural techniques can enhance cooling:

Embedded Heat Sinks: Using aluminum or copper heat sinks within the fuse holder.

Forced-Air Cooling: Incorporating fans to promote airflow.

Liquid Cooling: Deploying liquid-cooled designs for heavy-duty applications. For example, water-cooled fuse holders have demonstrated a 30% reduction in operating temperature.

4. Thermal Monitoring and Control

Advanced monitoring ensures safety and efficiency:

Temperature Sensors: Installing sensors at critical points for real-time monitoring.

Smart Control Systems: Leveraging IoT to trigger alarms or adjust loads under abnormal conditions.

Thermal Simulations: Using simulations to optimize design during development.

3. Real-World Applications

Example 1: High-Load Transformer Fuse Holder

For a 500A transformer, a specialized fuse holder was developed:

Material Choice: Silver-plated copper for conductors and thermally conductive polymers for housing.

Structural Design: Dual-layer heat sinks and thermal paste to enhance conduction.

Forced-Air Cooling: Integrated fan system to ensure consistent airflow.

Example 2: Heavy-Duty Industrial Robots

Robots operating in high-current environments require robust fuse holders:

Thermal Management: Ceramic substrates for superior heat resistance and liquid cooling for heavy loads.

Monitoring System: Sensors and IoT integration for predictive maintenance.

4. Future Trends

Smart Thermal Management: AI-driven systems for dynamic heat regulation.

Advanced Materials: Use of graphene and other nanomaterials for superior conductivity.

Modular Designs: Interchangeable components for flexible applications.

Green Solutions: Eco-friendly materials and designs to reduce energy consumption.

Conclusion

Thermal management is a cornerstone of high-current fuse holder design in industrial applications. By optimizing thermal pathways, employing advanced materials, and integrating intelligent monitoring systems, fuse holders can operate reliably under extreme conditions. As technology advances, future innovations will further enhance efficiency and sustainability, setting new standards for industrial electrical protection systems.

en.dghongju.com

[capybara-on-the-ezh]

preface: i'm not an expert on this; look into my sources (and find your own sources) because there's a chance i messed something up

i'm skeptical of the extraordinary claims here for a few reasons. firstly, generative ai is not a monolith, and it's well known that text generation is much less energy-intensive than image generation; this post disingenuously equates the two. secondly, it's not honest to ascribe the energy usage of data centers to ai--data centers are used for streaming video, hosting web or game servers, and other computational tasks. thirdly, the units here are strange--chatgpt using 17,000x the electricity of an american home sounds outrageous, but if you think about it, that's just the energy usage of a medium-sized city for a global, enormously popular service.

this seems like an objective, reasonable examination of ai energy usage:

it claims that:

generating 1,000 images with stable diffusion xl is equivalent to driving 4 miles in a gas car (so 1 image is equivalent to driving about 20 feet)

electricity usage from ai, cryptocurrency, and datacenters may double between 2022 and 2026 and may be responsible for about "one germany or sweden" worth of energy demand

rising electricity usage from ai is only a small part of electricity increases in general, compared to electric cars and industry

microsoft's increase in carbon emissions comes from building datacenters, not running ai models

similar claims about information technology using exorbitant amounts of energy in the past have not come to pass

the article cites this article with more specifics on individual energy usage:

which claims that:

generating one image with state-of-the-art models uses about as much energy as fully charging a smartphone

generating text 1,000 times uses 16% as much energy (in other words, generating one text uses 0.016% of the energy of charging a smartphone. i'm curious what "generating text" a certain number of times implies--is it per-prompt or per-token?)

larger, general models are more energy-demanding than smaller models trained on specific tasks (duh)

contrary to what i previously thought, training costs don't always outweigh usage costs--while usage costs are low, they add up, ans chatgpt's usage costs likely surpassed training costs in a couple of weeks

their source is this study, which wasn't peer-reviewed at the time:

finally there's this article, commenting on the same study with some useful comparisons for context:

it claims that:

1,000 text-classifications is equivalent in energy use to 9 seconds watching netflix, and 1,000 text-generations is equivalent to 3.5 minutes. this means that a single instance of text-generation would be equivalent to watching about a fifth of a second of netflix. that's not a lot, and you don't see people moralizing about the energy usage of netflix! i suspect that there's a bit of motivated reasoning going on when people moralize individual consumption of ai but not individual consumption of netflix or other technology.

however, they caution that the study is mainly useful for providing relative figures (image generation is orders of magnitude more costly than text generation) not absolute figures, because the testing isn't necessarily representative of how people actually use ai, and the computers that actually run these models at large scales are likely more optimized and efficient.

on a larger scale, a separate study claims that globally, ai could use as much energy as the netherlands, or about half a percent of global energy usage, by 2027

the author of this study cautions that energy usage from datacenters has historically been consistent, because increases in efficiency have balanced out increased demand. however, he says that because ai companies have been simply creating larger and larger models using more data, that this balancing may not hold because that's not conducive to efficiency

what do i personally make of this?

it seems to me like it's important to make a distinction between image generation (which is energy-intensive by all accounts) and text generation when looking at individual usage.

however, i am concerned by the total energy usage of ai, especially because the trend seems to be to create exponentially larger models with diminishing results instead of focusing on technological efficiency. i think that the choice for a company to use ai at a large scale (i.e. integrating it into search results or social media) needs to be carefully considered because it will increase energy usage.

however, i don't think it's useful to moralize individual usage of ai. i'm a vegan--i do moralize individual consumption like purchasing meat when it creates measurable harm for much smaller benefit, and when the demand fundamentally comes from the consumer. however, as i see it, the demand for ai comes from investors, not consumers--in fact, ai companies like openai and anthropic are operating at a loss from of their consumers' usage of their free products; they're willing to do this because they're betting on it becoming profitable in the future. unlike purchasing meat, using ai doesn't generate profit that goes toward producing more supply.

i also think that it's worth doing cost-benefit analysis--if some ai model used a large amount of electricity but was able to automate human dredgery or increase the efficiency of existing automation, that might be worth if! then of course you get into labor issues; ultimately under capitalism workers don't reap the benefits of automation. this, however, is an economic not technological issue, and applies equally to other forms of automation (like industrial robots).

there's also the social and aesthetic aspect of ai, which is ultimately the motivation for people moralizing it. here i largely agree with the anti-ai crowd (save for the copyright issue--ai is clearly transformative and doubling down on repressive copyright laws doesn't help artists)--i think that ai is overhyped, overused, often produces bad results, and can create social alienation when used to replace human connection. these are valid criticisms! however, this isn't reason to dismiss all generative ai--for some tasks (i.e. processing scanned text or generating image captions) ai excels and is, imo, genuinely worthwhile.

despite all of this, the energy usage of large-scale ai is still an issue. as explained before, this is not issue which can be addressed via consumer boycotts--ultimately, we need state regulation of large ai model training and deployment, and we urgently need to stop using fossil fuels. i think there's some hope on the sustainable energy front from the energy costs of ai--microsoft bought an exclusive license to use the three-mile island reactor, which could help offset increased energy usage. but we can't solely rely on the market for that; we need aggressive state action to accelerate and enforce the transition away from fossil fuels.

Idgaf if you don't want to write essays for school. I don't care if you don't want to write corporate emails yourself. I don't care if you can't draw well, I don't care if you can't write well, I don't care if you just really really want to talk to your favorite fictional character but don't want to RP with a real person because you have social anxiety or whatever

If you're still regularly using generative ai, chatgpt or midjourney or character.ai or literally whatever the fuck, im personally blaming you when my utility prices start going up.

[vermaaahna]

SAP Joule tutorial BAS extension in VS Code | SAP Generative AI | Access Joule from VS Code Using BAS Extension in VS Code we can configure the extension to connect with your SAP BAS environment by setting the endpoint and authentication details in the VS Code settings. Joule is a Generative AI assistant designed to create code for you. Each time you use the prompt, the generated code may vary, so the examples in the tutorial might not exactly match what you see on your system. Mail us on contact@anubhavtrainings.com Website: www.anubhavtrainings.com Phone No: +918448454549 https://www.youtube.com/watch?v=gcKPBeZmlpI

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I PARCHI EOLICI PRODUCONO UN RISCALDAMENTO DELL’ATMOSFERA!

L’articolo ”Climatic Impacts of Wind Power” di Lee Miller e David Keith, pubblicato il 10 aprile 2018 su Joule, evidenzia che l’energia eolica provoca impatti climatici non trascurabili, poiché genera energia elettrica estraendo energia cinetica dai venti diminuendone la velocità, e modificando scambio termico, umidità e quantità di moto fra la superficie e l'atmosfera. L’articolo fornisce una spiegazione meccanicistica degli impatti climatici delle turbine eoliche, su scala locale e globale, confrontando le simulazioni numeriche con le misurazioni strumentali al fine di colmare l'attuale lacuna fra gli studi di simulazione dell'energia eolica, e confrontandone i benefici ottenuti con gli impatti climatici. Gli autori hanno scoperto che se si generasse l'attuale domanda di energia elettrica degli Stati Uniti (0,5 TW) con l'energia eolica questa riscalderebbe le temperature superficiali degli Stati Uniti continentali di 0,24 °C. Un impatto sicuramente inferiore a quello dell'energia fossile che, però, impone la stima preventiva dell’impatto climatico prima di procedere con la decarbonizzazione e con la scelta fra le energie eolica e solare al fine di migliorarne la comprensione dei compromessi ambientali. Infatti tutte le fonti rinnovabili possono ”estrarre energia” solo ”alterando” i flussi energetici naturali, pertanto l'impatto sul clima è inevitabile anche se varia notevolmente in funzione del sistema di estrazione utilizzato.

Le differenze di temperatura diurne e stagionali calcolate dal modello matematico utilizzato sono sufficientemente coerenti con le recenti osservazioni di riscaldamento nei parchi eolici, anche se l’effetto di riscaldamento è:

a) Piccolo rispetto alle proiezioni del riscaldamento del XXI secolo;

b) Pressoché equivalente alla riduzione del riscaldamento ottenuta con la decarbonizzazione della produzione di energia elettrica globale;

c) Grande rispetto alla riduzione del riscaldamento ottenuta con la decarbonizzazione dell'energia elettrica statunitense con il vento.

Studi precedenti hanno valutato gli impatti climatici dell'energia idroelettrica, dei biocarburanti e dei sistemi solari fotovoltaici in rapida espansione della generazione di energia rinnovabile, pietra miliare degli sforzi per limitare i cambiamenti climatici decarbonizzando il sistema energetico mondiale. Oltre ai benefici per il clima, l'energia eolica e solare, in crescita di gran lunga superiore a quella delle altre fonti rinnovabili, riducono anche le emissioni di inquinanti critici (NOx, SOx e PM 2,5 ) e di inquinanti tossici come il mercurio, che hanno un impatto significativo sulla salute pubblica.

Anche studi precedenti sugli impatti climatici dovuti all'estrazione di energia eolica utilizzando modelli di circolazione generale (GCM), hanno rilevato impatti climatici statisticamente significativi all'interno del parco eolico, ma anche all'esterno, e talvolta di entità pari a quelli all'interno, non diversi dal riscaldamento provocato dai gas serra anche se in alcuni casi potrebbero contrastarne il conseguente riscaldamento, e hanno rilevato riduzioni sostanziali della velocità del vento e cambiamenti nello spessore dello strato limite atmosferico (ABL), oltre a differenze di temperatura, precipitazioni e scambi atmosferici verticali.

Gli autori intendevano valutare gli impatti climatici dell'energia eolica per unità di produzione energetica, ma questi dipendono dalla meteorologia locale e dalle teleconnessioni climatiche non locali, quindi dipendono fortemente dalla quantità e dal luogo di estrazione dell'energia eolica, vanificando lo sviluppo di una semplice metrica di impatto. Al fine di raggiungere una migliore comprensione delle politiche, hanno esplorato gli impatti climatici della generazione di 0,46 TW e di elettricità derivata dal vento negli Stati Uniti continentali, e hanno modellato una densit�� uniforme di turbine all'interno del terzo più ventoso degli Stati Uniti continentali., quindi una scala plausibile di generazione di energia eolica se questa svolge un ruolo importante nella decarbonizzazione del sistema energetico nella seconda metà di questo secolo.

In prospettiva, il tasso di generazione di elettricità del banco di prova (benchmark, in italiano) è circa 2,4 volte più grande del tasso di generazione di energia eolica negli Stati Uniti previsto per il 2050 dallo Studio centrale nella recente ”Visione del vento” del Dipartimento dell'Energia (DOE). Infine, è meno di un sesto del potenziale tecnico di energia eolica su circa le stesse aree ventose degli Stati Uniti stimate dal DOE.

In altre parole, noi vogliamo utilizzare le energie rinnovabili solare ed eolica per ridurre la concentrazione dei gas serra nella troposfera che vale il 3% dello 0,042%, quindi lo 0,00126% (!), dunque il riscaldamento globale antropogenico, ma per ottenere questo risultato utilizziamo parchi eolici che incrementano la temperatura locale (e globale), direttamente, di 0,24 °C, e parchi fotovoltaico che le incrementano molto di più!

Domenico Salimbeni, ingegnere.

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Un deficit strutturale e ambientale da cui non se ne esce. Alla fine, si torna sempre alla Termodinamica pura, ogni trasformazione di energia non adiabatica, cioè reale, genera una trasmissione di calore verso l’esterno. Quindi, più è alta la sua concentrazione, più conveniente, e meno inquinante, sarà la trasformazione stessa, per ogni kWh ottenuto.

Alessandro Olivo, ingegnere e professore presso l'università di Cagliari.