#automation

#automation

Python is one of the most popular programming languages for beginners because it is clear, readable, and used in almost every area of technology. Whether you want to explore automation, build simple tools, analyze data, or eventually move into machine learning, Python gives you a flexible and welcoming place to start. Many new learners begin with online coding courses to understand how Python works and why it is

After two years of experimentation, the material was finally right: a particular mix of thermoplastics and fibreglass that is strong, has no need of extra coating to protect it from sunlight, and is resistant to fouling and marine growth. The perfect base, says Mr Logtenberg, from which to 3D print a boat. Boats need to withstand the unforgiving nature of the marine environment.

There are exactly three meal-prep foods that I have on rotation: shredded beef, shredded pork, and, you guessed it, shredded chicken. All of these involve exactly two steps: Putting spices on a meat, and putting that meat into a crockpot. Every other dinner is leftovers or sandwich meat. Author Don't say I haven't tried. During the pandemic, I went through a jerky phase. I've sampled most of the meal prep boxes.

From human resources and operations to marketing and finance, systems ensure that every process, task, and decision fits into a larger framework of purpose and productivity. A well-designed business system transforms chaos into clarity, allowing teams to understand their roles, measure outcomes, and identify areas for improvement. Systems can be tangible, such as software and workflow tools, or intangible, such as organizational culture and communication protocols. Regardless of their type, their purpose remains the same: to create consistency and reliability.

In a new study, Gartner claimed AI will "touch all IT work by 2030" as enterprises ramp up adoption of new tools to drive productivity and alleviate strain placed on stretched IT teams. The extent of AI's influence in IT departments will vary, according to the consultancy. In a survey, CIOs said they expect around 75% of work to be done "by humans augmented with AI" by 2030, while around 25% of tasks will be carried out by AI alone.

Every single day-weekend, weekday, rain or shine-whichever robot vacuum I'm currently testing starts running at 9 am. It's always a good sign. I heave a sigh of relief and continue with whatever else I was doing, content that at least that f*cking chore in my house is getting done.

For Jan Gilg, SAP's co-chief revenue officer and head of the Americas market and the global Business Suite, thriving within today's economic climate and technology imperatives isn't about avoiding disruption. It's about using the agility those challenges cultivate to drive innovation. That can start with understanding what's proprietary about your business versus what's a process most businesses rely on. Gilg refers to this as "standardizing where you don't differentiate." In other words, automating standard processes that don't create value.

People working at the front and back offices of banks are going to have wildly different experiences with AI, says Sopnendu Mohanty, the group CEO of the global advisory and investment firm GFTN. He told Business Insider that the disruption posed by AI will depend on whether one works in a bank's front, middle, or back office. "Front is all for the customer. The middle is all for the bank, and the back is just for processing all the activity," Mohanty said.

The amount of money being spent on artificial intelligence is astronomical. Investors have lavished the top tech companies and startups alike with hundreds of billions of dollars - so much so, in fact, that an estimated 92 percent of US GDP growth now comes from AI. If trends continue in 2026, conservative estimates peg the spending from just the "largest technology firms" at $550 billion.

Many organizations are racing to build AI strategies, but too often they focus on adopting the latest tech, rather than creating the environment to support it. The reality is that lasting transformation is fueled by people, which requires companies to take a good look at their culture. At Architech, that's exactly what we did. By prioritizing and rewarding innovation, we aligned our culture with our AI strategy-and it worked.

DeepL calls its brand new Agent an AI-driven colleague. This assistant automates repetitive tasks, while the Customization Hub introduced today facilitates translation processes. In addition, DeepL has expanded its support with 70 new languages. DeepL Agent is available after extensive beta testing with more than 1,000 users. The tool performed 20,000 tasks during the test phase. The system automates tasks such as CRM management, customer service, and marketing activities, going far beyond the translation tasks you might associate with DeepL.

For years, automation has promised to make our lives easier - and to some extent, it has. But in 2025, things feel different. Traditional automation resembles a giant "if-else" statement that struggles to adapt to diverse situations. Agentic AI changes that narrative by enabling workflows to adjust and optimize themselves for countless scenarios that were difficult for older automation tools. In October 2025, OpenAI launched its AgentKit tool for building AI agents, and let me tell you, it is glorious!

Where the altruistic utopian designs of Buckminster Fuller provided an ideal for the first wave of Silicon Valley pioneers (a group including computer scientist and philosopher Jaron Lanier and Wired editor Kevin Kelly), later entrepreneurs have hewn closer to the principles of brilliant scientist and inventor Nikola Tesla, who believed, as he told Liberty magazine in 1935, that "we suffer the derangement of our civilization because we have not yet completely adjusted ourselves to the machine age."

If you're following me or decide to check out my profile after reading this, you'll notice something funny - there's exactly one post, and that too from 3 years ago. No, I wasn't dead, just alive and swimming hard in the AI race :). Things have gone too far - we all turned 3 more years older, but the world seems to have advanced 30 years ahead according to experts, I guess. ChatGPT became part and parcel of everything, everyone started chanting AI..AI..AI.

Businesses replacing human support agents with chatbots isn't new. Even before the AI chatbots of today, which are extremely common now, companies were using heavily engineered chatbots that could understand only certain keywords and respond with specific answers. They were terrible, but the one remarkable thing about them is that they showed us what different demographics really expect from customer support and set the standard for how AI-first helpdesks should work - not only in terms of support agents but support overall, including documentation.

Do, president of the East Side Union High School District board, will compete with Neysa Fligor, Yan Zhao and Rishi Kumar to replace longtime assessor Larry Stone in November's special election. If elected, Do said he plans to create a public dashboard with data on appeals and appraisal accuracy. "[Stone] may do it internally - and he may, he may not. I don't know, because it's internally," Do, 51, said. "But I'm willing to do that publicly."

But LLMs took it a notch even further, coders have started morphing into LLM prompters today, that is primarily how software is getting produced. They still must baby sit these LLMs presently, reviewing and testing the code thoroughly before pushing it to the repo for CI/CD. A few more years and even that may not be needed as the more enhanced LLM capabilities like "reasoning", "context determination", "illumination", etc. (maybe even "engineering"!) would have become part of gpt-9

Even the best artificial intelligence agents are fairly hopeless at online freelance work, according to an experiment that challenges the idea of AI replacing office workers en masse. The Remote Labor Index, a new benchmark developed by researchers at data annotation company Scale AI and the Center for AI Safety (CAIS), a nonprofit, measures the ability of frontier AI models to automate economically valuable work.

Many infrastructure and operations leaders aren't able to dig out enough money from budgets to reallocate to AI projects, Gartner said in a survey released this week. The research firm surveyed 253 IT leaders globally, and the budget issue plagued half the participants. As a result, 54% said they are focusing on AI projects with attainable results and foreseeable cost savings, Gartner said.