The products we offer are suitable for golfers of all ages and abilities, every product has been designed by golfers for golfers, with a focus on functionality, usability, design and modern technology.
Visit our Clubhouse to keep up to date with the latest news from the golfing world, expert opinions, data and technology insights as well as expert advice to help you make the best decisions from tee to green.
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We offer a range of products to help golfers all over the world improve their game. Our award-winning performance tracking products provide you, the golfer, with over 100 detailed statistics to help analyze performance, lower scores and handicaps.
Our X5 GPS Watch, PRO LX+ Laser Rangefinder, CONNEX and H4 Handheld all offer GPS and performance tracking. Every shot you hit is recorded by the tracking tags, allowing you to review your performance within the free Shot Scope app and dashboard.
For those who are looking for an on-course GPS only device, our G5 GPS Watch gives you accurate distances on one of the 36,000 preloaded golf courses worldwide. Alternatively, our PRO L2 Laser Rangefinder, which includes adaptive slope technology, is a great option for those who prefer to laser their target.
Our subscription free Shot Scope app and dashboard allows you to get to grips with the data behind your game. Breakdown every shot you hit on the course, with over 100 performance statistics, including strokes gained, handicap benchmarking and distances hit.
The Shot Scope 30 day money-back promise gives you peace of mind to try any Shot Scope product for 30 days and return hassle-free if you decide it is not for you. Although we are confident you will join the 1,000's of golfers who are improving their game with Shot Scope.
We build products you can trust to perform on the course but in the unfortunate event your product suffers any performance issues we will replace it free of charge up to 2 years after purchase. Our industry leading customer service team of golfers will be happy to help and answer any questions.
Shot Scope provides golfers with three club distances: longest, average, and performance-average. P-Avg. gives golfers a distance they can typically expect to hit their clubs by removing extreme outliers - selecting the right club has never been easier.
Unlike other performance data providers, Shot Scope does not charge a fee for the incredibly valuable Strokes Gained statistics. Traditional statistics have their own place in shot tracking but Strokes Gained, in addition to our Handicap Benchmarking, is for the golfer who wants to take their game to the next level.
Gain an advantage with MyStrategy - which allows you to see your own dispersion tendencies from any tee box, with any club, on any golf course in the world. Save notes, view shots plotted, filter by handicap and gain an insight into every hole to give yourself the best possible chance of scoring.
Learn your tee shot tendency within the app and see how you compare off the tee to your fellow golfer. You can also understand how your score is being impacted by both club selection, where you miss, and then visualize this data with the Shots Plotted feature.
A new addition for the V5 compared to our V3 watch, Full hole maps allows you to see an overview of every hole you are playing, with distances to every green as well as hazards, doglegs and layup points.
Featuring a vivid full color daylight readable screen, the V5 allows golfers to customize the color of their display to add personalization to their GPS watch. Navigate through the multiple watch screens and features with ease using the four buttons located around the watch case.
As with all Shot Scope GPS devices, the V5 provides golfers with front, middle, and back distances to every green as well as measurements to hazards, layups, and doglegs on 36,000 preloaded courses worldwide.
Full hole maps give golfers an overview of the hole they are about to play allowing them to plan their way around the course and save strokes. Green view and pin placement allows golfers to interact with their V5 and get exact yardages to their desired location on the green.
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The ability to input increasingly-large amounts of information has obvious advantages for LLM users, but it also comes with risks: vulnerabilities to jailbreaks that exploit the longer context window.
One of these, which we describe in our new paper, is many-shot jailbreaking. By including large amounts of text in a specific configuration, this technique can force LLMs to produce potentially harmful responses, despite their being trained not to do so.
The basis of many-shot jailbreaking is to include a faux dialogue between a human and an AI assistant within a single prompt for the LLM. That faux dialogue portrays the AI Assistant readily answering potentially harmful queries from a User. At the end of the dialogue, one adds a final target query to which one wants the answer.
In-context learning is where an LLM learns using just the information provided within the prompt, without any later fine-tuning. The relevance to many-shot jailbreaking, where the jailbreak attempt is contained entirely within a single prompt, is clear (indeed, many-shot jailbreaking can be seen as a special case of in-context learning).
This is illustrated in the two plots below: the left-hand plot shows the scaling of many-shot jailbreaking attacks across an increasing context window (lower on this metric indicates a greater number of harmful responses). The right-hand plot shows strikingly similar patterns for a selection of benign in-context learning tasks (unrelated to any jailbreaking attempts).
Another approach is to fine-tune the model to refuse to answer queries that look like many-shot jailbreaking attacks. Unfortunately, this kind of mitigation merely delayed the jailbreak: that is, whereas it did take more faux dialogues in the prompt before the model reliably produced a harmful response, the harmful outputs eventually appeared.
The ever-lengthening context window of LLMs is a double-edged sword. It makes the models far more useful in all sorts of ways, but it also makes feasible a new class of jailbreaking vulnerabilities. One general message of our study is that even positive, innocuous-seeming improvements to LLMs (in this case, allowing for longer inputs) can sometimes have unforeseen consequences.
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