5/2/2023 0 Comments Auto slash![]() Needless to say, if you’ve booked a rate that’s non-refundable, it’s not going to be worth using HotelSlash because even if they find a cheaper rate, you’d still be stuck paying for two rooms as you’d be paying for your original reservation regardless.Ģ) You might miss out on points, elite night credits, status benefits, etc. It’s not necessarily as great as it sounds though as there are all kinds of things that you need to take into account before rebooking your hotel through HotelSlash.ġ) It won’t work on non-refundable reservations If they do find a cheaper room rate, it can save you money. If they don’t find a lower room rate, you’re no worse off. It’s free, so it doesn’t cost you anything to forward your hotel reservations to them. Once you’ve made a new reservation, you’ll have to cancel the original reservation yourself. Instead, they’ll email you with the cheaper options. HotelSlash won’t automatically rebook your reservation if they find something cheaper. As a brief summary, once you’ve made a hotel reservation, you forward the confirmation email to They’ll track the room rates at the hotel and notify you not only if your specific room type drops in price, but also if other room types become cheaper which could potentially get you an upgraded room for a similar or lower price than you originally booked. It looks like it’s a promising service that can provide some decent savings, but there are some very important aspects of the service that are worth bearing in mind. ![]() This can provide significant savings without you having to manually check the price yourself every day.ĪutoSlash has recently launched a similar service for hotel bookings called HotelSlash. if you’re not familiar with it, AutoSlash is a service where you input details of your car rental reservation and they search for cheaper options all the way up to your day of rental. “This means manufacturers can bring new vehicles to market faster, which is vital to reach EV ambitions.If you ever use rental cars, there’s a good chance that you’ve heard of AutoSlash. “The Monolith platform empowers automotive R&D teams to use AI to learn the best possible insights from years of existing test data, or instantly predict results from a small sample of current tests,” Ahlfeld said. The platform can be applied to any industry that uses data and repetitive testing. Monolith was founded by NASA alumni CEO Richard Ahlfeld in 2016 and is poised to rapidly scale the tech thanks to $14.2M in funding from some of the world’s top software investors. Monolith has spent six years developing the platform, working alongside some of the engineering teams at some of the world’s leading auto manufacturers.Īmong those it claims have benefited are Honda, which recorded an 83% faster design cycle, and the Jota Sports Endurance Racing Team, which reduced the number of simulations and tests it conducted by 50% and associated costs by 66%. Monolith is leveraging this data to train AI self-learning models to accurately predict performance by interpreting vehicle systems’ behavior from the data, the AI helps engineers understand how vehicles react in areas that are currently impossible to simulate, as well as in different conditions.Īreas of the development process already being aided by the approach are wind tunnel testing, track testing, wheel and tire assessment, vehicle dynamics, durability, crash testing and powertrain appraisal. The company’s alternative is to make more use of the vast amounts of data produced by physical and simulation tests. While presently there is a reliance on a combination of physical and simulator testing, Monolith says this is inefficient because the accuracy of the latter can be limited, which means an increased number of physical tests are necessary to validate the results. Monolith claims its AI solution has the potential to “transform” the process by using new techniques. ![]() There is also less of a requirement to construct hugely expensive physical prototypes, meaning significant cost savings, while a reduction in on-road testing enhances sustainability, too. This ensures every element of the development process is accelerated, from the initial design to iterations, validation and production. The London-based firm says its tech uses self-learning models to instantly predict the results of complex vehicle dynamics systems, in the process reducing the need for physical tests or simulations. The length of time and cost involved in developing new cars could be halved in the future, thanks to an AI platform from software company Monolith.
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