#AI energy demand

[doughaugh]

Utilities Face 26% Demand Increase by 2028

A recent study from Bain and Company indicates that utilities will need to increase generation by 26% by 2028. After a couple of decades of flat load demand, we see a significant shift in demand. There seems to be even faster demand growth behind it. AI is the biggest contributor to growth at 44% of the expected demand growth. It is also having the most impact on how utilities respond. It was the…

[meteorologistaustenlonek]

"I always feared that the AI data center boom was likely going to make the looming #climatecatastrophe inevitable, but there was something about seeing it all presented on a platter with a smile and an excited presentation that struck me as more than just tone-deaf.

It was damn near revolting. I think the worst part of Huang's keynote wasn't that none of this mattered, it's that I don't think anyone in Huang's position is really thinking about any of this at all. I hope they're not, which at least means it's possible they can be convinced to change course. The alternative is that they do not care, which is a far darker problem for the world."

[cryptidafter]

if Oom was my sister, we'd have to fight, idc lol

[theclearblue]

Love my roommates truly and dearly but being told AI is the future and I have to accept it is top 5 most agonizing things I've ever heard in my entire life

[haveievermentioned]

I hate AI

AI is nothing more than a bunch of cyber bros masturbating over how they can now kill their english teacher who tried to teach them how to read and understand things. "Oh you can use it to summarize meeting" "You can use it to look up things" "Oh you are starting a Podcast about history? How are you using AI?" My job is integrating it on the back end and with that I can't opt out of it. Plus they never think about how if you need fewer people, then there are fewer jobs and therefore, fewer people who use your products BECAUSE THEY LITERALLY CAN'T AFFORD IT. I hate all of this all the time. I can't wait until it dies. At least my job is taking about how expensive it is so if people don't use it it's a waste. Guess what I will not use willingly!

[bitcoinversus]

Two Companies Eye $125 Billion AI Data Centers in North Dakota

Two unidentified companies have proposed building artificial intelligence (AI) data centers in North Dakota, with each project potentially costing up to $125 billion. This massive investment could transform the state’s tech infrastructure, marking it as a critical hub for AI-driven operations. During an August meeting with the North Dakota Public Service Commission, Commissioner of Commerce Josh…

[tekginger]

Big Tech’s Shift to Nuclear: A Sustainable Future For Artificial Intelligence

[newsepick]

Google backs new nuclear plants to power AI

Google is partnering with nuclear startup Kairos Power to construct seven small nuclear reactors in the U.S., a groundbreaking deal aimed at supporting the company's growing energy needs for AI and promoting a nuclear revival. The agreement, which includes a commitment to purchase 500 megawatts of power, marks the first commercial initiative for small modular reactors in the U.S. Kairos plans to deliver the reactors between 2030 and 2035, using molten fluoride salt instead of water as a coolant. This partnership addresses the demand for stable, carbon-free energy in the tech industry.

[public-cloud-computing]

Gen AI streamlines resource allocation, saving costs and boosting efficiency. Explore how it optimizes your business operations.

[rubylogan15]

Gen AI streamlines resource allocation, saving costs and boosting efficiency. Explore how it optimizes your business operations.

[enterprise-cloud-services]

See how Gen AI drives cost-efficient resource allocation with its data-driven approach, optimizing operations and cutting unnecessary expenses.

[generative-ai-in-bi]

How Does Gen AI Make Resource Allocation Cost-Efficient?

Find out how Gen AI enhances cost-efficiency in resource allocation with cutting-edge algorithms and data insights for smarter business decisions.

In the contemporary business world, strategy implementation requires proper management of resources to sustain organizational competitiveness. Resource allocation is a critical capability for today’s businesses as it enables efficient and effective resource usage as a way of optimizing profits and reducing costs. However, most traditional techniques for resource allocation are defective since the data used are either inaccurate or insufficient to exact resource optimizations. This is where Generative AI (Gen AI) comes into play. Gen AI is revolutionizing the way businesses approach the management of their resources through increased efficiency, operational costs, and responsiveness to changing market conditions, all due to its use of sophisticated algorithms and access to large quantities of data.

Generative AI offers a new dimension in the concept of cost because they make data as the center of resource management plans. Through its real-time analysis of large datasets, Gen AI can help businesses make better decisions on the deployment of their resources. In terms of inventory, workforce, or supplies, Generative AI guarantees the spending of available resources to the least possible extent. As mentioned above the advantages of implementing Gen AI in resource management is not a pipe dream; there are already companies across industries that are realizing lower operational costs and higher efficiency.

Predictive Analytics for Demand Forecasting

The most significant application of Generative AI in the allocation of resources is its predictive analytics use in demand forecasting. Gen AI uses historical data to make persistent analyzes and draw the corresponding conclusion of future demand for products and/or services. It is most applicable in the management of inventory since both overstocking and stock-outs can be very costly. Overstocking means keeping excess inventory leads to the consumption of company capital, and stock-outs lead to lost business and customers’ disappointment. This is where Generative AI can help with demand forecasting, allowing businesses to have just the right amount of stock which is optimal for fulfilling customer needs without overstocking.

For example, a retailer leveraging Gen AI for demand forecasting can plan for increased demand of certain products during festive occasions and replenish their stock in advance. This approach reduces the probability of overstocking, but also helps to avoid stock-outs and hence the use of resources and costs are optimized. Within industries like manufacturing where raw materials and production schedules need to be carefully managed, Generative AI can forecast fluctuations in demand and optimize the supply chain as well, further reducing costs and improving efficiency.

Optimizing Workforce Allocation

There are other important area like workforce management where Generative AI can drive significant cost efficiencies. Typically, workforce management often involves manual scheduling, and this causes some problems such as high levels of inefficiency in utilization of labor resources, which include time wastage and over-time costs. As for generative AI, it is capable of identifying workforce needs of a company based on project requirements, skills and workload balances. This way, it avoids issues such as over staffing, which may lead to wastage of resources, or understaffing that may slow down productivity.

For example, in a manufacturing plant, Gen AI is capable of estimating peak and off production seasons and then schedule the employees. For instance, the AI could recommend hiring additional workers during peak production periods as well as downsizing during slower periods. Such a level of precision in workforce allocation not only reduces idle time and overtime expenses but also enhances overall productivity. Several companies that have integrated AI in workforce management solutions have realized better control of workforce costs and increased employees’ satisfaction since the workforce is well-matched with the business needs.

Enhancing Supply Chain Efficiency

Supply chain management usually involves a cocktail of issues including supplier selection, logistics, and inventory management which all have the tendency of contributing to the over cost of the overall chain. The innovation of generative AI presents a powerful solution to these challenges since it improves the transparency and flow of supply chain. Gen AI is also very effective in analyzing data from all supply chain links from the procurement of raw materials to final product delivery; Gen AI can identify cost-effective suppliers, optimize logistics routes, and streamline inventory management.

For instance, Generative AI can analyze historical data to identify the best suppliers regarding delivery time, quality, and price in the supply chain. It also simplifies the process of finding new sources and can help to negotiate for better prices and improved supply chain reliability. As for the concept of logistic, Gen AI can easily find the best routes to transport goods, reducing fuel consumption and delivery times, which directly translates into cost savings. Further, by providing real-time insights into inventory levels, Generative AI is also important in eliminating excess stock and stock out situations hence increasing the efficiency of the supply chain and decrease operational costs.

Dynamic Pricing Models with Gen AI

Dynamic pricing is a method through which prices for products and services are varied according to the current market conditions. Generative AI helps to integrate flexible pricing strategies into enterprises with high levels of accuracy based on market changes. Having information about the customer behavior, competitor actions, and broader economic trends, Gen AI can suggest the optimal price adjustments that balance competitiveness with profitability.

For instance, an e-commerce platform with Gen AI to apply dynamic pricing will reduce product prices during low demand in the market in order to increase its sales revenue, and increase prices during high demand to increase its profits. This flexibility in pricing helps businesses want to remain relevant and at the same time make profits without having to compromise on its profit margins. Companies that have adopted the use of AI in pricing strategies have disclosed that they have realized an increase in revenue and profit margins, as they are able to respond more quickly and effectively to market changes.

Energy Consumption and Sustainability

The cost of energy consumption for a business is one of its significant expenses depending on the industry where it operates, specifically those relying heavily on energy, such as manufacturing industries and other sectors utilizing large amounts of energy. As for the challenges and the solutions, there are still some challenges to be addressed that lead to Generative AI’s major advantage of improving efficiency in energy consumption and leading to cost reduction for renewable energy, which in turn makes a positive impact toward achieving sustainability. Because the patterns of energy use, equipment performance, and production schedule can be monitored and analyzed, Gen AI can suggest changes to optimize energy use and increase efficiency.

For example, in the manufacturing environment, Gen AI can use data from sensors installed in manufacturing equipment to identify low energy consumption time and recommend changes to the schedules or equipment settings. This not only lowers energy costs but also supports the company’s sustainability initiatives by reducing its carbon footprint. Industries like automotive manufacturing where energy cost forms a good fraction of the total cost have already started realizing benefits of AI-driven energy management with companies recording improvements in energy consumption of more than 20%.

Risk Management and Cost Control

It is crucial to function as a risk management practice since uncontrolled risks may significantly impact the company’s profitability. Generative AI plays a crucial role in risk management, as it helps to determine risks before they occur and provides recommendations on how to avoided them. Using historical data, trends, and various indicators, Gen AI can predict potential disruptions and recommend ways of preventing or mitigating them.

For instance, in the financial sector of a business, Gen AI can look at the market tendencies, identify emerging economic risks that might affect either a company’s investment or operations. Through early identification of these risks, the AI enables the management to make necessary changes, including adjusting investment portfolios or resource allocations, to minimize loss. This proactive approach not only lowers the probability of losses, but also helps in better dealing with the budget management, as the resources can be distributed with more precision if the risks are taken into consideration.

Continuous Learning and Improvement

One of the major benefits of Generative AI is that it expands and develops a model while working on it. Unlike traditional systems, Gen AI receives new data more often and updates its algorithms for efficient resource allocation. This continuous learning process makes certain that the AI in cost management is always up to date achieving further improved levels of effectiveness and efficiency.

For example, in a retail context, Gen AI might initially analyze sales data to optimize inventory levels. As the customer data and seasonal trends are accumulated or the conditions of competition changes, the AI system would move to more effective recommendations of solution making the whole process cost saving and more efficient. Such continuous improvement process plays an important role in contemporary business environment in order to cope up with emerging business environments.

Conclusion

This is what generative AI is doing for businesses as it brings efficiency, flexibility, and profitability to resource management. Besides, more operational expertise, workforce and supply chain management, flexible pricing, and risk management allow Gen AI to greatly contribute to cost cutting and increased effectiveness. With the progressing advancement of Generative AI systems, it will be to businesses’ advantage to allocate the power of this technology to resource management. It is for this reason that cost management of the future is already here, and it is driven by Generative AI.

Original Source : https://bit.ly/4grgQU7

[dieterziegler159]

How Does Gen AI Make Resource Allocation Cost-Efficient?

See how Gen AI drives cost-efficient resource allocation with its data-driven approach, optimizing operations and cutting unnecessary expenses.

See how Gen AI drives cost-efficient resource allocation with its data-driven approach, optimizing operations and cutting unnecessary expenses. In the contemporary business world, strategy implementation requires proper management of resources to sustain organizational competitiveness. Resource allocation is a critical capability for today’s businesses as it enables efficient and effective…

[nudityandnerdery]

Guy says he's wanted to see a live action version of Princess Mononoke for over twenty years. So, instead of spending time learning to make films and about cinematography and actually creating his own art?

He dumped some money into an AI generator to make a shot for shot remake of the trailer.

Dude decided the best way he could pay tribute to an iconic movie about the importance of the relationship between humanity and nature was to recreate it in a manner that includes no human actors and is an industry that is notoriously demanding devastating amounts of energy in the middle of a fucking climate crisis, this shit is beyond parody.

[snekdood]

people always gotta lot to say about comic artists and about how they need to be "posting more frequently" but you sit them down and tell them to do the same shit and suddenly they're "unprepared", etc. 🙄 yknow this shit doesnt get shat out over night, right? find a hobby in the meantime while you wait, goddamn.