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From quick-fire quizzes to immersive multiplayer experiences, PlayLink titles are all about social gaming that everyone can enjoy. Pop a game into your PS4, use your smartphone or tablet as a controller, gather around your TV and prepare for a refreshingly different experience.
Just Deal With It! delivers a whole new twist on five classic card games. Play Poker, Blackjack, Crazy Eights, Rummy and Hearts locally or on-line. Team up with friends and family, launch attacks, sabotage the competition, and go all in for the win in this riotous card game party!
Rhythm and coordination are the key to success in Melbits World, a cute and colourful collaborative puzzle-platformer. Collect and guide the digital creatures through a series of fiendish levels by teaming up with friends to control platforms, obstacles and traps; all that while dodging viruses, gathering seeds and spreading good vibes across the internet.
Simple, elegant gameplay and intense strategy come together in Ticket to Ride, the railway-themed board game now on PlayLink. Collect various types of trains and use them to claim railway routes across the map. The longer the routes, the more points you earn!
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On Monday, June 2, 2008 Jonathan Siegrist, 22, made the third ascent of Grand Ole Opry at the Monastery, Colorado. Originally rated 5.14a by its creator,Tommy Caldwell, the climb was uprated to 5.14c by Andy Raether after he did the second ascent, in 2007. UPDATE: On July 7, 2008 Siegrist made the third ascent of Country Boy (5.13d) at Lumpy Ridge, placing all of the gear on lead (perhaps the first ascent done in this style?) Stay tuned for more details. Climbing hard and under the radar, Siegrist, a full-time student at Naropa University and routesetter at the Boulder Rock Club, did the route in just around 10 days.
Siegrist: I climb with my father all the time; he is like my number one climbing partner. We have 100% support for one another. He has hiked hours with a heavy pack to projects with me to give me a belay in crappy weather and even skipped work to do so. I have done the same for him (although surely not as much). Climbing together has made us into even better friends and also solid training partners that push one another.
Siegrist: Each generation no doubt has something different to offer the other. I think climbing with my dad and his buds has made me humble and well rounded, while him climbing with my friends and me has made him try harder and go outside his comfort zone. We each appreciate the other greatly for this.
Siegrist: The longer the route, the more climbing! Beautiful lines inspire and technical routes take a certain dedication that I find really rewarding. Plus I am much more technical than I am purely strong. Old school lines are always the most aesthetic because the old school climbers had free reign on loads of untouched rock.
Siegrist: Grand Ole Opry is a striking line on an amazing orange wall at the Monastery here in Colorado. The route climbs the longest section of the slightly overhanging wall through an improbable series of ultra technical movement on poor holds. It has three distinct cruxes, each one harder than the last that are separated by okay rests and finishes with an enduring section of 5.12+. It is excellent.
Siegrist: absolutely love the area and I was always with really good friends climbing there. There were 4 old rotting elk legs scattered along the trail that were in a new location every day. We made hilarious and detailed jokes about the legs dancing at night to pass the time hiking in. Whenever we hiked in with dogs they would run ahead to fetch the elk legs and run up and down the trail carrying them, banging us in the calves with the rotting legs as they passed by. It was really funny at times.
Siegrist: I have done a number of long alpine and multipitch routes, but just recently I have become much more interested in hard one-pitch trad climbs. It is for sure the next frontier for me- there are so many amazing trad routes around here and most of my sport projects are getting cleaned up.
Climbing: Tell me a bit about your studies at Naropa? Why is it important to you to get an education even while keeping climbing at a hard level? Have you considered just climbing full-time, or would that not be enough to keep you interested?
Siegrist: I have been fortunate to travel quite a bit and in the last few years I have also been climbing when abroad. I moved to Northern Thailand in the last half of 2006 and climbed a bunch in the Chiang Mai area with some really good friends of mine there. I also took a wild exploratory trip to Cambodia that Nov / Dec, we found some amazing boulders and also climbed a huge slab in the middle of nowhere- it was crazy. I have climbed a bit around the rest of South East Asia and a little in Europe also. My dad and I did a killer high altitude big wall in Peru a few years back in addition to some cool mountaineering there.
Siegrist: For the mean time I am stoked on trying hard trad stuff and lots of climbing in Rocky Mountain National Park up high, but no specific projects until the fall. I have some unfinished business up at the Industrial Wall to take care of.
A technique for evaluating the importance of a featureor component by temporarily removing it from a model. You thenretrain the model without that feature or component, and if the retrained modelperforms significantly worse, then the removed feature or component waslikely important.
For example, suppose you train aclassification modelon 10 features and achieve 88% precision on thetest set. To check the importanceof the first feature, you can retrain the model using only the nine otherfeatures. If the retrained model performs significantly worse (for instance,55% precision), then the removed feature was probably important. Conversely,if the retrained model performs equally well, then that feature was probablynot that important.
A/B testing usually compares a single metric on two techniques;for example, how does model accuracy compare for twotechniques? However, A/B testing can also compare any finite number ofmetrics.
Accelerator chips (or just accelerators, for short) can significantlyincrease the speed and efficiency of training and inference taskscompared to a general-purpose CPU. They are ideal for trainingneural networks and similar computationally intensive tasks.
Binary classification provides specific namesfor the different categories of correct predictions andincorrect predictions. So, the accuracy formula for binary classificationis as follows:
Although a valuable metric for some situations, accuracy is highlymisleading for others. Notably, accuracy is usually a poor metricfor evaluating classification models that processclass-imbalanced datasets.
For example, suppose snow falls only 25 days per century in a certainsubtropical city. Since days without snow (the negative class) vastlyoutnumber days with snow (the positive class), the snow dataset forthis city is class-imbalanced.Imagine a binary classificationmodel that is supposed to predict either snow or no snow each day butsimply predicts "no snow" every day.This model is highly accurate but has no predictive power.The following table summarizes the results for a century of predictions:
In a neural network, activation functions manipulate theweighted sum of all the inputs to aneuron. To calculate a weighted sum, the neuron adds upthe products of the relevant values and weights. For example, suppose therelevant input to a neuron consists of the following:
A training approach in which thealgorithm chooses some of the data it learns from. Active learningis particularly valuable when labeled examplesare scarce or expensive to obtain. Instead of blindly seeking a diverserange of labeled examples, an active learning algorithm selectively seeksthe particular range of examples it needs for learning.
A sophisticated gradient descent algorithm that rescales thegradients of each parameter, effectively giving each parameteran independent learning rate. For a full explanation, seethis AdaGrad paper.
More generally, an agent is software that autonomously plans and executes aseries of actions in pursuit of a goal, with the ability to adapt to changesin its environment. For example, LLM-based agents might use theLLM to generate a plan, rather than applying a reinforcement learning policy.
The process of identifying outliers. For example, if the meanfor a certain feature is 100 with a standard deviation of 10,then anomaly detection should flag a value of 200 as suspicious.
A non-human mechanism that demonstrates a broad range of problem solving,creativity, and adaptability. For example, a program demonstrating artificialgeneral intelligence could translate text, compose symphonies, and excel atgames that have not yet been invented.
A non-human program or model that can solve sophisticated tasks.For example, a program or model that translates text or a program or model thatidentifies diseases from radiologic images both exhibit artificial intelligence.
Formally, machine learning is a sub-field of artificialintelligence. However, in recent years, some organizations have begun using theterms artificial intelligence and machine learning interchangeably.
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