AI Research
Why Power Plants Need AI That Engineers Can Trust

America’s power producers face growing pressure to do more with less. A rapidly evolving grid, increasing demand, aging infrastructure, and policy uncertainty have created a system where traditional approaches to reliability are no longer enough.
The North American Electric Reliability Corporation (NERC) recently issued its 2025 RISC report, highlighting the leading risks facing America’s power sector. NERC warns that outdated planning assumptions, infrastructure interdependencies, and unpredictable weather are stretching the system beyond what it was designed to handle.
COMMENTARY
This is also coming at a time when President Trump has emphasized the grid’s importance to America’s artificial intelligence (AI) industry and national security.
And yet, some grid operators are relying on legacy methods, making dispatch decisions in silos without seeing the larger picture, and need to spend resources inspecting aging infrastructure. This approach must change to meet the growing power demand from building electrification, data centers, factories, and electric vehicles.
Power producers have a generational opportunity to use AI to drive intelligence-driven, anticipatory operations.
That’s where knowledge graph–based systems come in. Unlike traditional analytics tools that operate within single datasets or pre-programmed rules, graph-based AI connects the dots across a wide array of operational inputs (sensor data, outage records, fuel logistics, weather forecasts, maintenance logs, market pricing data, etc). By adopting trustworthy AI systems, leaders can identify subtle patterns, anticipate stress points, and support predictive decision-making.
NERC’s recent report emphasized the rising risk of interdependent infrastructure failure, such as a gas supply interruption that could cascade into generation outages. AI platforms that understand these cross-sector linkages help plant operators see around corners, identifying vulnerabilities and enabling smarter resource allocation before risks materialize.
Or consider predictive maintenance. AI systems that fuse real-time inputs with historical failure trends and environmental conditions can flag issues with accuracy and direct human crews to where they’ll have the most impact. This has been used effectively in the oil and gas industry for offshore drilling to help managers know when their equipment needs to be replaced.
This is not about replacing human expertise. If a plant entirely outsourced its thinking to an AI model, NERC would face an entirely new set of risks around AI hallucination-enabled power crises.
Instead, the best AI platforms are those that let users explore the “why” behind a recommendation, run accurate scenarios based on available knowledge, and compare the AI’s data with their own experience.
This is another advantage of the knowledge-graph-based approach. Analysts can dissect exactly how their AI reached a particular conclusion or recommendation by following the literal connections between data that the AI used. In comparison, a traditional database could spit out an answer without a source, and the user is unable to verify if it is accurate.
Large Language Models that keep their data in a “black box” have had a history of prominent incidents where the models have been blamed for potentially hallucinating everything from scientific papers that do not exist, to fake medical codes for hospitals, to made-up quotes submitted in a legal brief, among many other examples.
Blindly trusting AI is not the answer, but the power generation industry can leverage the energy it produces for AI to make the very generators that fuel it even smarter. Without this strategic approach, companies miss out on reaping the rewards of their generators powering massive AI data centers.
We’ve entered an era where siloed systems no longer suffice. If power producers want to stay ahead of aging infrastructure, growing demand, and unpredictable stressors like supply chain disruptions for fuel sources such as natural gas or coal, they need to invest in AI.
Explainable and traceable AI can help grid operators create an environment where human insight and machine intelligence reinforce each other. This symbiotic relationship adds an entirely new layer of resilience to the power grid, transforming how we think about energy generation and management.
—Jon Brewton is CEO of Data Squared.
AI Research
The impact of artificial intelligence on the food industry

The integration of artificial intelligence (AI) into the food industry is revolutionizing the way food is produced, processed, distributed, and consumed. AI-driven solutions offer unprecedented opportunities for improving efficiency, ensuring safety, reducing waste, and enhancing sustainability in this vital sector. This article explores how AI is transforming various facets of the food industry, from farm to table.
AI in agriculture
The food production process begins on the farm, where AI technologies are helping farmers make smarter decisions. Precision agriculture, powered by AI, uses data from sensors, drones, and satellites to monitor crop health, soil conditions, and weather patterns. Machine learning algorithms analyze this data to provide actionable insights, such as when to irrigate, fertilize, or harvest crops. This approach not only boosts yield but also minimizes the use of water, fertilizers, and pesticides, reducing environmental impact.
Robotics is another AI application making waves in agriculture. Autonomous tractors and robotic harvesters equipped with AI can perform labor-intensive tasks with precision, addressing labor shortages and reducing costs. For instance, AI-enabled robots can differentiate between ripe and unripe fruits, ensuring only the best produce is picked.
Enhancing food processing and manufacturing
AI is playing a critical role in food processing and manufacturing by optimizing operations and ensuring quality control. Advanced vision systems powered by AI can inspect food products for defects, contaminants, or inconsistencies at a speed and accuracy unmatched by human workers. This ensures that only safe and high-quality products reach consumers.
Predictive maintenance is another area where AI is proving invaluable. By monitoring machinery and analyzing operational data, AI can predict equipment failures before they occur, minimizing downtime and maintenance costs. This level of foresight is especially important in food manufacturing, where delays can lead to spoilage and significant financial losses.
In addition to improving efficiency, AI-driven automation is enhancing worker safety by taking over hazardous tasks, such as handling hot or sharp equipment. This contributes to creating a safer work environment in food processing plants.
Supply chain optimization
The food supply chain is a complex network that requires precise coordination to ensure timely delivery of perishable goods. AI-powered tools are streamlining supply chain management by improving forecasting, inventory management, and logistics.
Demand forecasting is a key application of AI in this domain. By analyzing historical sales data, market trends, and external factors like weather or holidays, AI systems can accurately predict demand for different food products. This helps retailers and suppliers avoid overstocking or understocking, reducing food waste and increasing profitability.
AI is also revolutionizing logistics through route optimization and real-time tracking. Advanced algorithms can determine the most efficient delivery routes, reducing fuel consumption and ensuring products reach their destinations as quickly as possible. Additionally, AI can monitor the condition of perishable goods during transit, ensuring they remain within safe temperature ranges.
Enhancing food safety and quality
Food safety is a top priority in the industry, and AI is proving to be a powerful ally in this area. Machine learning algorithms can analyze vast amounts of data from production lines, environmental monitoring systems, and lab tests to identify potential risks or contamination sources.
AI-powered tools are also aiding in the rapid detection of pathogens like Salmonella and E. coli. Traditional testing methods can take days, but AI-based systems can deliver results in hours, enabling quicker responses to potential outbreaks. Moreover, blockchain technology combined with AI is enhancing traceability, allowing stakeholders to track the journey of a product from farm to fork. This transparency helps build consumer trust and simplifies recalls in case of contamination.
Reducing food waste
Food waste is a significant global issue, and AI is offering innovative solutions to address this challenge. AI systems can analyze data from supermarkets, restaurants, and households to identify patterns and suggest ways to reduce waste. For instance, AI can recommend optimal stock levels for retailers, ensuring they do not overorder perishable items.
In the hospitality sector, AI-powered tools can monitor inventory and predict demand, helping chefs prepare just the right amount of food. This not only reduces waste but also cuts costs. Additionally, AI is being used to repurpose surplus food by identifying ways to incorporate it into new recipes or distribute it to those in need.
Personalized nutrition and consumer experience
AI is transforming the way consumers interact with food, offering personalized recommendations based on individual preferences, dietary restrictions, and health goals. Apps and wearable devices equipped with AI can analyze user data to suggest meal plans, track nutritional intake, and even offer cooking tips.
Retailers are also using AI to enhance the shopping experience. AI-powered chatbots and virtual assistants can guide customers in selecting products, answer queries, and provide tailored suggestions. Meanwhile, AI-driven shelf management systems ensure that popular items are always in stock, improving customer satisfaction.
Driving sustainability
Sustainability is a pressing concern for the food industry, and AI is helping companies adopt greener practices. By optimizing resource usage, reducing waste, and improving supply chain efficiency, AI is enabling the industry to lower its carbon footprint.
AI is also playing a role in developing alternative proteins, such as plant-based or lab-grown meat. Machine learning models are being used to optimize formulations, improve texture and taste, and scale production. These innovations are contributing to a more sustainable and ethical food system.
Challenges and future prospects
While the benefits of AI in the food industry are immense, challenges remain. High implementation costs, lack of technical expertise, and concerns about data privacy are some of the barriers to widespread adoption. Additionally, there is a need for robust regulations to ensure ethical use of AI and address potential biases in decision-making.
Despite these challenges, the future of AI in the food industry looks promising. As technology continues to evolve, we can expect even more sophisticated applications that further enhance efficiency, sustainability, and consumer satisfaction. Companies that embrace AI today will be well-positioned to lead the industry into a smarter, more sustainable future.
In conclusion, AI is not just a tool but a transformative force reshaping the food industry. By harnessing its potential, stakeholders can address some of the most pressing challenges in food production, safety, and sustainability, ultimately creating a better food system for everyone.
AI Research
Google plots further £5B UK AI invest…

Google used the opening of a data centre in the UK to commit another £5 billion to its local operations, focusing on AI research for the science and healthcare sectors and predicting it would support a little more than 8,000 jobs each year.
The company stated the opening of the data centre in the south of the UK forms part of a two-year investment spanning capex, R&D and associated engineering.
In a statement, it hailed the moves as “another milestone” in its commitment to the AI sector in the UK.
It was a view echoed by Rachel Reeves, the Chancellor of the Exchequer, who opened the data centre and said Google’s investment “is a powerful vote of confidence in the UK economy”.
The politician also emphasised a strengthening of ties with the US resulting from the investment, which she said would create “jobs and economic growth for years to come”.
Most news organisations highlighted Google’s pledge came on the same day US President Donald Trump is due to arrive in the UK for a state visit: Reuters reported an expectation there would be a brace of other such deals agreed during the two-day stay.
Crux
Google emphasised the home-grown credentials of its latest data centre, stating more than 250 companies were involved in building it, “the majority of them local”. The facility was built to meet demand for its Cloud, Workspace, Search and Maps services.
Some of the £5 billion it now plans to invest will go towards Google DeepMind AI R&D, with the company emphasising benefits to the UK’s economy and cybersecurity, along with job creation.
Ruth Porat, president and chief investment officer of Google and its parent Alphabet, estimated AI could add £400 billion to the UK economy by 2030, a potential she argued her company is helping unlock along with “enhancing critical social services”.
Google unveiled a carbon free energy management arrangement with Shell Energy Europe it stated would “contribute to grid stability” by focusing on clean power creation and access to battery storage systems.
The company stated the arrangement with Shell and its other clean energy initiatives in the UK could result in its operations running “at or near 95 per cent carbon-free-energy in 2026”.
AI Research
UK to receive $6.8B Google investment for AI development

Google, part of Alphabet Inc., revealed its intention to invest £5 billion, approximately $6.8 billion, in the UK specifically to boost the development of an AI economy in the country in the next two years.
The tech giant shared this significant plan just as the US President Donald Trump gets ready to disclose economic deals surpassing $10 billion. This was brought during Trump’s visit to the US’s long-standing ally this week.
Google and AI rivals fuel UK tech surge
Not all the investment will be dedicated to the above sector; some will be set aside for a newly developed data center in Waltham Cross that focuses on meeting the surging demand for Google’s services, such as map and search services. According to the tech giant, this investment is a game-changer that will create about 8,250 jobs for UK citizens annually.
Just like Google, its rivals in the AI race, OpenAI and Nvidia, are also eyeing the UK to make investments worth billions in the country’s data centers during Trump’s visit.
According to reports, the investment will be implemented in collaboration with Nscale Global Holdings Ltd. Nscale is a London firm that operates large scale data centers and is a major player in Europe’s growing demand for AI infrastructure.
Trump’s visit to the UK strengthens the economies of the two nations
Earlier on September 15, senior officials in the US revealed that the American president was planning to announce economic deals exceeding $10 billion during his second visit to the United Kingdom.
“The trip to the U.K. is going to be incredible,” Trump told reporters Sunday. He said Windsor Castle is “supposed to be amazing” and added: “It’s going to be very exciting.”
The visit will feature a collaboration in science and technology, a sector anticipated to bring billions in new investments. The officials who shared these details about Trump’s trip wished to remain anonymous due to the confidential nature of the discussion.
They also stated that there is a likelihood that Trump and Keir Starmer, UK’s Prime Minister, might announce a defense technology cooperation deal and boost relationships between major financial centers in the two countries.
Some of these economic deals may be announced during a business reception that Rachel Reeves, the Chancellor of the Exchequer, will host, where the two leaders will be present. Other top US tech executives attending the event include Jensen Huang from Nvidia, and Sam Altman from OpenAI. They will participate in roundtable talks on Thursday, September 18, at Chequers, the prime minister’s residence.
These economic programs came alongside previous efforts to sign a significant deal that would ease the construction of nuclear power plants. The two countries will utilize each other’s safety checks on reactor designs that will accelerate the approval process.
Even though some economic deals are progressing smoothly, US officials have highlighted that Trump’s announcements will likely not include a deal to loosen US tariff policies on scotch whiskey. Notably, this is what Starmer has been actively pushing for.
The officials also pointed out a likelihood that the announcements will not address Trump’s ongoing worries brought about by the UK government’s ability to regulate US-based tech firms such as Apple and Alphabet, in connection with their control over smartphones.
Get seen where it counts. Advertise in Cryptopolitan Research and reach crypto’s sharpest investors and builders.
-
Business3 weeks ago
The Guardian view on Trump and the Fed: independence is no substitute for accountability | Editorial
-
Tools & Platforms1 month ago
Building Trust in Military AI Starts with Opening the Black Box – War on the Rocks
-
Ethics & Policy2 months ago
SDAIA Supports Saudi Arabia’s Leadership in Shaping Global AI Ethics, Policy, and Research – وكالة الأنباء السعودية
-
Events & Conferences4 months ago
Journey to 1000 models: Scaling Instagram’s recommendation system
-
Jobs & Careers3 months ago
Mumbai-based Perplexity Alternative Has 60k+ Users Without Funding
-
Podcasts & Talks2 months ago
Happy 4th of July! 🎆 Made with Veo 3 in Gemini
-
Education3 months ago
VEX Robotics launches AI-powered classroom robotics system
-
Education2 months ago
Macron says UK and France have duty to tackle illegal migration ‘with humanity, solidarity and firmness’ – UK politics live | Politics
-
Podcasts & Talks2 months ago
OpenAI 🤝 @teamganassi
-
Funding & Business3 months ago
Kayak and Expedia race to build AI travel agents that turn social posts into itineraries