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A Game of Box Office Predictions. Update: During this podcast, we put the call out to listeners/readers to create a system that would act as a running scoreboard, dynamically updating with the box office numbers to show who is in the lead throughout the Summer. A /Filmcast listener named Paul answered the call, and you can now check the running tally on the Summer Movie Wager Virtual Scoreboard.

We didn’t actually expect anyone to create anything as intricate as this, so a big thanks goes out to Paul. Please also check out his cocktail blog here. Its that time of year again — the Summer movie season is upon us. And the /Filmcast team have once again gathered to compete in what has become an annual tradition: the Summer Movie Wager. Every year in the past I would make a guest appearance on the Totally Rad Show for this segment, but with that show now disbanded we have taken on the job of hosting this contest on /Film. This is the tenth annual edition of this contest.

Last year was David Chen’s first time participating and he won the wager. This year the contest includes Devindra Hardawar (his first time), David Chen, Germain Lussier, Jeff Cannata and myself in a game is to decide what will be the highest grossing films of the Summer.

September 30, 2016. FOR TODAY'S BELIZE WEATHER, CLICK HERE. Click for our Daily Tropical Weather Report. Specials and Events. Last night's TV news on Channel 7.

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It’s a free- for- all; the person with the best score wins. But it isn’t just that easy — not only do the participants need to predict what 1.

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After the jump you can listen to the full episode of the show with our predictions. Summer Movie Wager Podcast: Download or play now in browser: 2.

Summer Movie Wager Rules. The rules for the game come from Time. Travel. Review’s Summer Movie Pool: The object is to pick the films that you think will be the top- ten grossing films of the summer, in order of box- office performance. As I’ve said, that means only films released from May 1st 2.

Labor Day weekend, counting only the money those films make domestically (US and Canada) in that period. In other words films from March or April might still be making money after May 1st, but they don’t count; films released from May on could start racking up foreign B. O., but that doesn’t count; films released from May on could still be making money into September, but that doesn’t count either.

Box Office numbers are generally available late Monday or Tuesday after the weekend closes. For the last seven or so years, I have been using box office numbers from Yahoo Box Office which gets their numbers in turn from Box Office Mojo. So what you will be doing is figuring out what 1. BUT, in addition to your top 1. Dark Horses”- films you think *might* make it, but that you are not confident enough about to put into the top 1. Summer Movie Wager Scoring: Getting number 1 or number 1. The rest of the scoring goes like this: 1.

Top 1. 01 point for each dark horse that makes it into the Top 1. The scoring is tabulated so that you get the SINGLE HIGHEST point value for each pick- that is, if you get number ten right, you don’t get 1. Peter Sciretta’s List: Finding Dory. Captain America: Civil War. Suicide Squad. Independence Day: Resurgence.

X- Men: Apocalypse. Ghostbusters. The Secret Life of Pets. Star Trek Beyond. Alice Through the Looking Glass. Teenage Mutant Ninja Turtles: Out of the Shadows.

Wildcards. Ice Age: Collision Course. Neighbors 2. Warcraft. David Chen’s List. Captain America: Civil War. Finding Dory. Secret Life of Pets. Suicide Squad. X- Men Apocalypse.

Star Trek Beyond. Jason Bourne. Ghostbusters. Independence Day: Resurgence. Ice Age: Collision Course.

Wild Cards: Germain Lussier’s List: Captain America Civil War. Finding Dory. Independence day. Secret Life Pets.

X- men. Alice. Central Intelligence. Ghostbusters. Suicide Squad.

Star Trek Beyond. Wildcards. Neighbors 2. Ninja Turtles 2. Conjuring 2. Jeff Cannata’s List: Civil War. Finding Dory. Ice Age. Xmen Apocalypse. Independence Day. Download The New Cas And Dylan Poster (2015) Movie on this page. TMNTJason Bourne.

Star Trekghostbusters. Suicide Squad. Wildcards. Neighbors 2. Central Intelligence. Pete’s Dragon. Devindra Hardawar’s List: Captain America Civil War. Suicide Squad. The Angry Birds Movie. X- Men Apocalypse. The Secret Life of Pets.

Finding Dory. Jason Bourne. Star Trek Beyond. Independence Day Resurgence. Ghostbusters. Wildcards.

Central Intelligence. The BFGFree State of Jones. Feel free to make your own predictions in the comments below! Cool Posts From Around the Web.

Artificial intelligence - Wikipedia. Artificial intelligence (AI, also machine intelligence, MI) is intelligence exhibited by machines, rather than humans or other animals (natural intelligence, NI). In computer science, the field of AI research defines itself as the study of .

Many tools are used in AI, including versions of search and mathematical optimization, neural networks and methods based on statistics, probability and economics. The AI field draws upon computer science, mathematics, psychology, linguistics, philosophy, neuroscience, artificial psychology and many others. The field was founded on the claim that human intelligence . With his Calculus ratiocinator, Gottfried Leibniz extended the concept of the calculating machine (Wilhelm Schickard engineered the first one around 1. Since the 1. 9th century, artificial beings are common in fiction, as in Mary Shelley's Frankenstein or Karel . The study of mathematical logic led directly to Alan Turing's theory of computation, which suggested that a machine, by shuffling symbols as simple as . This insight, that digital computers can simulate any process of formal reasoning, is known as the Church–Turing thesis.

Marvin Minsky agreed, writing, . Progress slowed and in 1.

Sir James Lighthill and ongoing pressure from the US Congress to fund more productive projects, both the U. S. The next few years would later be called an . By 1. 98. 5 the market for AI had reached over a billion dollars. At the same time, Japan's fifth generation computer project inspired the U. S and British governments to restore funding for academic research. The Kinect, which provides a 3. D body–motion interface for the Xbox 3.

Xbox One use algorithms that emerged from lengthy AI research. Clark also presents factual data indicating that error rates in image processing tasks have fallen significantly since 2. Other cited examples include Microsoft's development of a Skype system that can automatically translate from one language to another and Facebook's system that can describe images to blind people.

The general problem of simulating (or creating) intelligence has been broken down into sub- problems. These consist of particular traits or capabilities that researchers expect an intelligent system to display.

The traits described below have received the most attention. The search for more efficient problem- solving algorithms is a high priority. Many of the problems machines are expected to solve will require extensive knowledge about the world. Among the things that AI needs to represent are: objects, properties, categories and relations between objects.

A representation of . The semantics of these are captured as description logic concepts, roles, and individuals, and typically implemented as classes, properties, and individuals in the Web Ontology Language. Such formal knowledge representations are suitable for content- based indexing and retrieval, scene interpretation, clinical decision support, knowledge discovery via automated reasoning (inferring new statements based on explicitly stated knowledge), etc.

Video events are often represented as SWRL rules, which can be used, among others, to automatically generate subtitles for constrained videos. For example, if a bird comes up in conversation, people typically picture an animal that is fist sized, sings, and flies. None of these things are true about all birds. John Mc. Carthy identified this problem in 1. Almost nothing is simply true or false in the way that abstract logic requires. AI research has explored a number of solutions to this problem.

Research projects that attempt to build a complete knowledge base of commonsense knowledge (e. Cyc) require enormous amounts of laborious ontological engineering—they must be built, by hand, one complicated concept at a time. For example, a chess master will avoid a particular chess position because it . These are non- conscious and sub- symbolic intuitions or tendencies in the human brain. As with the related problem of sub- symbolic reasoning, it is hoped that situated AI, computational intelligence, or statistical AI will provide ways to represent this kind of knowledge. This calls for an agent that cannot only assess its environment and make predictions, but also evaluate its predictions and adapt based on its assessment.

Emergent behavior such as this is used by evolutionary algorithms and swarm intelligence. Supervised learning includes both classification and numerical regression. Diary Of A Wimpy Kid The Long Haul (2017) Free Download on this page.

Classification is used to determine what category something belongs in, after seeing a number of examples of things from several categories. Regression is the attempt to produce a function that describes the relationship between inputs and outputs and predicts how the outputs should change as the inputs change. In reinforcement learning. The agent uses this sequence of rewards and punishments to form a strategy for operating in its problem space. These three types of learning can be analyzed in terms of decision theory, using concepts like utility.

The mathematical analysis of machine learning algorithms and their performance is a branch of theoretical computer science known as computational learning theory. A sufficiently powerful natural language processing system would enable natural language user interfaces and the acquisition of knowledge directly from human- written sources, such as newswire texts. Some straightforward applications of natural language processing include information retrieval, text mining, question answering. Although these indexes require a large volume of user input, it is expected that increases in processor speeds and decreases in data storage costs will result in greater efficiency. Perception. Computer vision.

A few selected subproblems are speech recognition. Intelligence is required for robots to handle tasks such as object manipulation. These systems require that an agent is able to: Be spatially cognizant of its surroundings, learn from and build a map of its environment, figure out how to get from one point in space to another, and execute that movement (which often involves compliant motion, a process where movement requires maintaining physical contact with an object). It is an interdisciplinary field spanning computer sciences, psychology, and cognitive science. While the origins of the field may be traced as far back as the early philosophical inquiries into emotion, the more modern branch of computer science originated with Rosalind Picard's 1.

First, being able to predict the actions of others by understanding their motives and emotional states allow an agent to make better decisions. Concepts such as game theory, decision theory, necessitate that an agent be able to detect and model human emotions. Second, in an effort to facilitate human- computer interaction, an intelligent machine may want to display emotions (even if it does not experience those emotions itself) to appear more sensitive to the emotional dynamics of human interaction. Creativity. For example, even specific straightforward tasks, like machine translation, require that a machine read and write in both languages (NLP), follow the author's argument (reason), know what is being talked about (knowledge), and faithfully reproduce the author's original intent (social intelligence).

A problem like machine translation is considered . Researchers disagree about many issues.?

Or is human biology as irrelevant to AI research as bird biology is to aeronautical engineering?? Or does it necessarily require solving a large number of completely unrelated problems?? Or does it require . Computational psychology is used to make computer programs that mimic human behavior. Some of them built machines that used electronic networks to exhibit rudimentary intelligence, such as W.

Grey Walter's turtles and the Johns Hopkins Beast. Many of these researchers gathered for meetings of the Teleological Society at Princeton University and the Ratio Club in England.