Latest news with #efficiency
The Independent
an hour ago
- Business
- The Independent
Will a heatwave help your solar panels perform better?
High temperatures can slightly reduce the efficiency of solar panels, despite longer daylight hours increasing overall generation. solar panels perform optimally at 25 degrees Celsius or below, with efficiency decreasing by approximately 0.34-0.5 percentage points for each degree above this temperature. During the UK's record 40.3°C heatwave in July 2022, good solar panels operated at about 5 per cent below their peak efficiency. Despite the heat, the commercial solar sector performed well during the record heatwave, contributing 8.6 per cent of the UK's electricity needs that day. Investing in solar panels can be beneficial for homeowners, with payback periods ranging from 5 to 13 years depending on factors like system size, roof orientation, and electricity usage patterns. solar panels have a long lifespan of up to 30 years, making them a viable long-term investment, especially with future heatwaves expected to be longer and hotter in the UK.
Fast Company
2 days ago
- Business
- Fast Company
Are you not entertained? The next frontier of brand entertainment
In partnership with Omnicom, Jeff Beer sits down with Patty Morris, the head of brand at State Farm; Erwin Dito, the VP of global brand leadership at McDonald's; and Jae Goodman, the founder and CEO of Superconnector Studios, to discuss why effectiveness and efficiency are not the same thing in the advertising world.
Forbes
2 days ago
- Business
- Forbes
20 Expert Tips To Avoid Network Automation Pitfalls
Network automation offers the promise of greater efficiency, faster deployments and fewer manual errors—but it's not without its challenges. Many teams dive in with good intentions, only to encounter roadblocks that stall progress, introduce complexity or even create security gaps. The good news is that many common pitfalls are avoidable with the right planning, tools and processes. Below, members of Forbes Technology Council highlight mistakes they've seen in network automation efforts and share practical tips to help your team get it right from the start. A common network automation pitfall is automating without fully understanding existing network workflows. This can cause outages or security gaps. Teams can avoid these issues by documenting processes, validating configurations in a test environment, and involving network engineers early in automation planning. - Sai Shashank Rasamalla, American Express A common pitfall is automating without fully understanding the existing network architecture and dependencies. This can lead to unintended outages or security gaps that keep getting missed because there is no human intervention. - Venkata Thummala, Stanford Health Care Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify? A common network automation pitfall is failing to document configuration changes in real time. This can lead to misconfigurations and delays in troubleshooting. IT teams can avoid this by using tools that automatically track and update network changes, ensuring visibility and control as automation scales. - Douglas Murray, Auvik A common network automation pitfall is ad hoc scripting without standardization. Ad hoc scripts solve short-term problems but create long-term complexity and fragility. Adopting infrastructure as code avoids this by enforcing version control and modularity and ensuring only authorized, trackable changes are deployed, bringing stability, security and team alignment. - Karan Alang, Versa Networks Inc. A common network automation pitfall is relying on code-heavy solutions that only a few engineers can maintain, limiting scalability and resilience. Embracing no-code automation allows more team members to build and manage workflows, reduces reliance on novice coding skills, and ensures consistent, scalable network operations. - Song Pang, NetBrain Technologies A common network automation pitfall is inadequate testing of scripts before deployment, potentially causing outages. To avoid this, teams should create a testing environment that mimics production, use version control for scripts, conduct code reviews, automate testing processes and implement gradual rollouts, like canary releases. Additionally, proper documentation and training on automation tools are needed. - Raghvendra Tripathi Here's one I've seen recently: the use of weak or recycled security keys during automated deployments. These systems often don't generate strong randomness, making networks vulnerable. Teams can avoid this by using secure key generators or hardware-based tools that ensure fresh, strong encryption keys every time. - Erick Grau, Chibitek A frequent pitfall is automating overly complex or poorly understood manual processes—essentially, 'paving the cowpath.' Teams create brittle automation, which is a nightmare to maintain. Avoid this by first standardizing and simplifying the target process. Then, automate in small, incremental, well-tested steps. Focus on foundational elements before tackling intricate workflows. - Ashish Bhardwaj, Google Automating outdated legacy networks is like racing with a cracked engine. Without modern foundations, automation amplifies fragility and will lead to further complexities later on. Standardizing configurations and leveraging AI-driven workflows by upgrading ineffective systems will build resilient and intelligent networks. - Savinay Berry, OpenText One network automation pitfall is to simply automate a bad process; it just fails faster. Automation requires rethinking—not just for today, but for tomorrow—in a new, inventive way to anticipate technology growth and changes so that solutions stay relevant longer. - Pam Brodsack, Velera A common network automation pitfall is inadequate data backup verification. Many teams automate backups but don't periodically validate their integrity or restorability—until disaster strikes. Implement regular automated test restorations alongside your backup routines to verify that data can actually be recovered. This ensures your backups will work when really needed. - Chongwei Chen, DataNumen, Inc. A common network automation pitfall is alert overload from static, context-poor data. To avoid this, teams should integrate rich telemetry with AI-driven analysis to provide contextual, actionable alerts. This reduces noise and makes the process of identifying the root cause more streamlined, which ultimately supports more effective and efficient automation. - Judit Sharon, OnPage Corporation One common network automation pitfall is ignoring cross-team collaboration. When networking, security and operations teams work in silos, automation efforts often conflict or fail. To avoid this, build cross-functional workflows early on, ensuring alignment, shared goals and integrated feedback loops for smooth execution. - Rishi Kumar, MatchingFit One of the most frequent mistakes in network automation is rushing to automate processes without a structured plan. Teams often deploy automation tools haphazardly—scripting repetitive tasks or adopting orchestration platforms without evaluating long-term scalability, security or operational dependencies. - Pratik Badri, JPMorgan Chase & Co A common pitfall in network automation is a disconnect among processes, people and technology. Successful implementation requires these elements to work in harmony. Over-automation can alienate those who struggle to keep pace with rapid tech changes. Processes should be designed with adaptability and leverage technology when appropriate, not be dictated by it. - Hari Sonnenahalli, NTT Data Business Solutions Config drift is a major pitfall—manually applied changes bypass automation, causing inconsistencies. Modern teams avoid this by implementing strict automation-only policies, using tools like GitOps for infrastructure as code, and integrating validation checks that detect manual changes. Treating configs as immutable through CI/CD pipelines ensures all changes are tracked and reversible. - Anuj Tyagi One common pitfall is neglecting decommissioning. Automation excels at spinning up, but stale configs, orphaned services and zombie routes linger. Teams must automate clean-up, too—expiry policies, lifecycle hooks and teardown scripts ensure networks stay lean, secure and scalable. Don't just build—declutter. - Roman Vinogradov, Improvado Overlooking scalability is a frequent network automation pitfall; solutions that work for small environments may fail as networks grow. Teams can avoid this by designing automation with scalability in mind from the outset—using modular, reusable code and regularly reviewing automation tools to ensure they can handle increased complexity and volume as the organization expands. - Pradeep Kumar Muthukamatchi, Microsoft A common pitfall in network automation is treating it as tactical 'patchwork' rather than strategic orchestration. Many organizations automate isolated tasks without considering how those actions fit into the broader operational value chain, leading to fragmented solutions. To avoid this, step back and assess the entire operational workflow—identify dependencies, control points and outcomes. - Anil Pantangi, Capgemini America Inc. Skipping rigorous validation is a top network automation pitfall; a single typo or misconfiguration deployed at scale can cascade into massive outages. To prevent this, teams should embed pre- and post-change checks using network simulators, peer-reviewed scripts, automated verification tests and enforced rollback logic, ensuring errors are caught and reversed before they spread. - Sai Sandeep Ogety,
Associated Press
2 days ago
- Business
- Associated Press
Amazon CEO Jassy says AI will reduce its corporate workforce in the next few years
Amazon CEO Andy Jassy anticipates generative artificial intelligence will reduce its corporate workforce in the next few years as the online giant begins to increase its usage of the technology. 'We will need fewer people doing some of the jobs that are being done today, and more people doing other types of jobs,' Jassy said in a message to employees. 'It's hard to know exactly where this nets out over time, but in the next few years, we expect that this will reduce our total corporate workforce as we get efficiency gains from using AI extensively across the company.' The executive said that Amazon has more than 1,000 generative AI services and applications in progress or built, but that figure is a 'small fraction' of what it plans to build. Jassy encouraged employees to get on board with the e-commerce company's AI plans. 'As we go through this transformation together, be curious about AI, educate yourself, attend workshops and take trainings, use and experiment with AI whenever you can, participate in your team's brainstorms to figure out how to invent for our customers more quickly and expansively, and how to get more done with scrappier teams,' he said. Earlier this month Amazon announced that it was planning to invest $10 billion toward building a campus in North Carolina to expand its cloud computing and artificial intelligence infrastructure. Since 2024 started, Amazon has committed to about $10 billion apiece to data center projects in Mississippi, Indiana, Ohio and North Carolina as it ramps up its infrastructure to compete with other tech giants to meet growing demand for artificial intelligence products. The rapid growth of cloud computing and artificial intelligence has meanwhile fueled demand for energy-hungry data centers that need power to run servers, storage systems, networking equipment and cooling systems. Amazon said earlier this month that it will spend $20 billion on two data center complexes in Pennsylvania. In March Amazon began testing artificial intelligence-aided dubbing for select movies and shows offered on its Prime streaming service. A month earlier, the company rolled out a generative-AI infused Alexa. Amazon has also invested more heavily in AI. In November the company said that it was investing an additional $4 billion in the artificial intelligence startup Anthropic. Two months earlier chipmaker Intel said that its foundry business would make some custom artificial intelligence chips for Amazon Web Services, which is Amazon's cloud computing unit and a main driver of its artificial intelligence ambitions.
The Independent
2 days ago
- Business
- The Independent
Amazon CEO Jassy says AI will reduce its corporate workforce in the next few years
Amazon CEO Andy Jassy anticipates generative artificial intelligence will reduce its corporate workforce in the next few years as the online giant begins to increase its usage of the technology. 'We will need fewer people doing some of the jobs that are being done today, and more people doing other types of jobs,' Jassy said in a message to employees. 'It's hard to know exactly where this nets out over time, but in the next few years, we expect that this will reduce our total corporate workforce as we get efficiency gains from using AI extensively across the company.' The executive said that Amazon has more than 1,000 generative AI services and applications in progress or built, but that figure is a 'small fraction' of what it plans to build. Jassy encouraged employees to get on board with the e-commerce company's AI plans. 'As we go through this transformation together, be curious about AI, educate yourself, attend workshops and take trainings, use and experiment with AI whenever you can, participate in your team's brainstorms to figure out how to invent for our customers more quickly and expansively, and how to get more done with scrappier teams,' he said. Earlier this month Amazon announced that it was planning to invest $10 billion toward building a campus in North Carolina to expand its cloud computing and artificial intelligence infrastructure. Since 2024 started, Amazon has committed to about $10 billion apiece to data center projects in Mississippi, Indiana, Ohio and North Carolina as it ramps up its infrastructure to compete with other tech giants to meet growing demand for artificial intelligence products. The rapid growth of cloud computing and artificial intelligence has meanwhile fueled demand for energy-hungry data centers that need power to run servers, storage systems, networking equipment and cooling systems. Amazon said earlier this month that it will spend $20 billion on two data center complexes in Pennsylvania. In March Amazon began testing artificial intelligence-aided dubbing for select movies and shows offered on its Prime streaming service. A month earlier, the company rolled out a generative-AI infused Alexa. Amazon has also invested more heavily in AI. In November the company said that it was investing an additional $4 billion in the artificial intelligence startup Anthropic. Two months earlier chipmaker Intel said that its foundry business would make some custom artificial intelligence chips for Amazon Web Services, which is Amazon's cloud computing unit and a main driver of its artificial intelligence ambitions.
