Latest news with #Segato
Hamilton Spectator
6 days ago
- Business
- Hamilton Spectator
Trek Bicycle Burlington nabs Ontario ‘best bike business' honour
A Burlington bicycle shop is on the Ontario By Bike 2025 list of best Ontario bike businesses. Trek Bicycle Burlington store manager Chris Segato said the store has operated in its current location for about three years. Segato said the store was previously known as Neworld Cycle for 30 years in Burlington, before it was sold to Trek Bicycle. He said the recognition 'speaks to the credibility of our staff.' Segato said Trek currently employs nine full and part-time staff, including avid cyclists, with experience in the bike industry, interested in supporting customer purchases and goals whether they are high-end racers, or just want to cycle local trails. 'We want everyone feeling wanted, heard and appreciated,' Segato said. More information on Wisconsin-based Trek Bicycles is available on the company's website . The store-specific web page includes the 560 Plains Rd. E. location's hours and contact information. The non-profit organization Transportation Options operates Ontario By Bike and annually recognizes bike businesses like bike stores and bike-friendly businesses like coffee shops, attractions and accommodations. One business is recognized in each category, by provincial tourism regions including Hamilton-Halton-Brant — where Trek Bicycle Burlington got a nod this year. It was the only Halton region business on the list this year. The full list of this year's winners across Ontario, and annual lists back to 2019, are available on the Ontario By Bike website . Louisa Mursell, executive director of Transportation Options, said Ontario By Bike works with a variety of partners to develop and promote cycling and cycle tourism across Ontario. 'Administering a network of over 1,656 certified bicycle friendly businesses and providing a comprehensive portal of information, Ontario By Bike is inspiring visitors and residents to explore more of the province by bike,' Mursell said. Mursell said the 1,656 businesses certified as 'bike friendly' within Ontario By Bike's network have the opportunity to nominate themselves, or be nominated by cyclists, for a bike friendly business award each year. The certification criteria for various types of businesses is available on the Ontario By Bike website. Mursell said Trek Burlington was selected as best bike business in Hamilton-Halton-Brant because:
Forbes
28-04-2025
- Business
- Forbes
The Agents Are Coming – More On What We Will Do Next To AI Partners
If the prior year was the year of artificial intelligence becoming more familiar to the average person, and the rise of certain brand names, like ChatGPT, this year is the year of the AI agent. In a nutshell, this is the idea that LLM engines can go beyond just predicting words or simulating conversation, and start doing things themselves. Some of Anthropic's Claude tools are an excellent example of the AI taking more initiative and doing more on its own. At MIT, researchers are working on something called the AI agent index that maintains a database of agentic AI systems, exploring how AI agents are used for things like research, software development, and more. A resource from our CSAIL lab shows some of the major benefits of AI agents, including efficiency, specialization, and lower operational costs (more on that in a moment). The article also has a list of MIT notables handling projects related to agentic AI, including the work of my colleague Daniela Rus, the director of CSAIL MIT, in integrating natural language processing for self-driving vehicles. It lists challenges, too, and takeaways for business. It's a good survey. Here's another interesting source for direction on agentic AI. In a recent edition of AI Daily Brief, Nathaniel Whittemore goes over an essay by Gian Segato about new kinds of companies that will leverage technology in specific ways. 'A new breed of companies is emerging, lean, unconventional and wildly successful,' Segato writes. 'They generate hundreds of millions of dollars, yet have no sales teams, no marketing departments, no formal HR, not even vertically specialized engineers. They're led by a handful of people doing the work of hundreds, leveraging machines to scale their impact. For years, we feared automation would replace humans, but as AI reshapes the economy, it's becoming clear that far from replacing human ingenuity, AI has amplified it.' Segato also goes over a version of what can make AI 'agentic,' related to human ingenuity. 'True agency is an unruly psychological trait,' he writes. 'It's the willingness (to do things) without explicit validation, instruction or even permission. It's the meme you can just do things knowing that you could poke life and something will pop out the other side.' As Whittemore reads Segato's essay, outsourcing this task to an Elevenlabs voice approximator, the listener hears a thesis taking shape – that AI is changing the calculus on specialized labor. Noting that the past has 'not been kind to generalists,' Segato describes a shift where specialized human knowledge is going to become less valuable, too: 'We're now facing a rupture, a phase transition. AI has eroded the value of specialization, because for many tasks, achieving the outcome (that previously took) several years of experience, it now takes a $20 ChatGPT subscription … a decade ago, it took me nine months to gain enough experience to ship a single prototype. Now it takes just one week to build a state-of-the-art platform ready to be shipped, a project once only achievable by a full team of professionals.' It will change the way training works, he posits, and may result in many companies favoring credentials over outcomes. In the course of the essay, Segato uses terms like 'homeostatic equilibrium' to describe an environment disrupted by AI, and 'bimodal shape distribution of deployment,' noting that we might trend toward a need for 'specialized human accountability' in managing these agents. 'This will include sectors such as defense, healthcare, space exploration, biological research and AI administration itself,' Segato writes, 'all domains where variance of prediction models are higher than the acceptable risk threshold. Wherever mistakes can kill, and AI can't prove to be virtually all-knowing, we can expect regulation to enforce natural barriers and the need to hire experts. It's similar to why we continue to require human pilots: despite having the technological capacity for autonomous flight, sometimes we just want the ability to point a finger.' On the other hand, he describes situations where iterative failure toward success is an option, writing: 'Wherever we are okay with trying again after getting a bad AI generation, we will see market disruption. Data science, marketing, financial modeling, education, graphic design, counseling and architecture will all experience an influx of non-specialized, high-agency individuals. Sure, machines will keep making mistakes, but their rate of improvement has been astronomical and will only continue to delay the point at which generalists feel the need to hire experts.' After reading the entire piece, Whittemore provides some words of his own, after the obligatory vendor snippets. 'I think it's a great piece,' he starts out, 'very thought provoking, and I'm really excited that Gian has shared it and gotten us all to chatter.' Whittemore referred to a 'Microsoft work trend index' leading to a prediction of a time when humans plan, and AI executes. '(The index) basically predicted that the end state of agents In the office is human orchestrators and agent operators, basically, that humans were going to do the planning, and that agents were going to do the execution. That's a different way of saying that the key skill sets and attributes of people in the workforce in the future is going to be around planning and coordination of agents everywhere (that agentic AI) becomes popular.' He also weighs in on that difference between mission-critical applications and others that have room for error. 'We're even seeing this sort of division in the way that companies are experimenting with agents right now,' Whittemore says. 'There are certain parts of their business where they simply can't abide (the) current fail rate or hallucination rate or underperformance rate, or however you want to determine it, of agents, because it's so critical. On the other hand, there are areas where the consequence of those problems is simply less pertinent. It is in those consequence-light areas that companies are (using) agents now, with the knowledge that capabilities continue to trend up.' Listening to the podcast and looking at the components of the essay. I realize that a lot of the same ideas that we saw in conferences earlier this year are sounding out around the near future. I'm hearing a lot of experts talking about these likelihoods as AI develops rapidly. We'll have AI agents baked into various industries and verticals, and humans will have to figure out how to adapt and coexist with these tools. What will that change do in the context of classical business and its power relationships? We'll have to see.
