Syracuse football injury report: Foster, Pickard probable; Black, Coleman doubtful for Clemson matchup

first_imgSyracuse sophomore strong safety Evan Foster and and redshirt sophomore defensive lineman Jake Pickard are probable for Syracuse’s (3-3, 1-1 Atlantic Coast) matchup Friday night against No. 2 Clemson (6-0, 4-0), SU revealed Wednesday evening in its weekly injury report. Defensive back Josh Black and defensive lineman Kendall Coleman are doubtful for the third consecutive game.Foster missed most of the Pittsburgh game last week with an undisclosed injury. Coleman had racked up 18 total tackles in the season’s first four games, but he suffered an apparent right foot or ankle injury at then-No. 25 LSU.Linebacker Shyheim Cullen is also probable, while defensive lineman Shaq Grosvenor is doubtful. Wide receiver Sean Avant, defensive back Antwan Cordy and tight end Kyle Kleinberg are ruled out.On Monday, Syracuse second-year head coach Dino Babers provided an update on Cordy, a redshirt junior safety who has been out since the first quarter of the season. Cordy has “zero chance” to play this week and his future status is unclear. He has played all of eight quarters over the past two seasons after finishing second in tackles in 2015.Meanwhile, Clemson quarterback Kelly Bryant, who was originally questionable, The Greenville News reported, will play Friday, Clemson announced in its injury report. Bryant left Clemson’s game against Wake Forest during the third quarter last week with an ankle injury. The junior wore a protective boot.AdvertisementThis is placeholder textBryant has been the Tigers’ leading catalyst this season, averaging 277 yards per game while completing 67.3 percent of his passes and rushing for a team-leading 401 yards and seven touchdowns. The Daily Orange profiled the signal-caller as he stepped into Deshaun Watson’s footsteps.Kickoff between the defending national champion Clemson Tigers and Syracuse Orange is slated Friday for 7 p.m. The game will air on ESPN.Here’s the full Syracuse injury report:ProbableLB Shyheim CullenLB Shyheim CullenDB Evan FosterDL Jake PickardDoubtfulDL Josh BlackDL Kendall ColemanDL Shaq GrosvenorOutWR Sean AvantDB Antwan CordyTE Kyle KleinbergOut for the SeasonOL Aaron Roberts (knee) Comments Published on October 11, 2017 at 7:39 pm Contact Matthew: mguti100@syr.edu | @MatthewGut21 Facebook Twitter Google+last_img read more

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Women’s volleyball takes down sixth-ranked Washington

first_imgJunyi Li | Daily TrojanThe women’s volleyball team welcomed No. 6 Washington to the Galen Center on Sunday, as USC geared up for a stiff challenge from the reigning Pac-12 champions. Though the two teams battled closely throughout the match, the Women of Troy pulled off an upset in style, sweeping the Huskies in three sets with scores of 25-20, 25-21 and 28-26.A Trojan upset didn’t seem imminent, however, when Washington found itself up 19-16 late in the first set. But USC turned the tables with a 9-1 run to shock the Huskies with an opening-set victory. Senior opposite hitter Brittany Abercrombie, senior opposite hitter Niki Withers and sophomore outside hitter Khalia Lanier combined for six kills in the final 7 points to swing the momentum in their favor to begin the match.The Women of Troy rode similar bursts to a win in the second set. Three unanswered points broke a 5-5 tie, and another 3-0 run gave USC the edge when Washington tied the set at eight apiece. The Trojans didn’t relinquish their advantage from that point, and they took the second set 25-21.The final set was a much tighter affair, as the Huskies tied the score seven times after USC edged in front. But the Women of Troy refused to fall behind, even as the set extended past 25 points. They came up short in 3 match points, but senior middle blocker Jordan Dunn came up with a kill to set up a fourth. Finally, an ace from Withers sealed a 28-26 third-set win and sent the Huskies home. With the victory, USC rose to No. 15 in the AVCA Coaches poll while Washington slipped to No. 9.The Women of Troy were unable to take a single set against Washington when the two teams met last season, but they returned the favor in 2017 thanks to a balanced attack. Abercrombie recorded 13 kills, Withers put down 12 kills and Lanier added 11 more. Abercrombie’s strong day, combined with her 13-kill match against Washington State on Saturday, earned her Pac-12 Offensive Player of the Week honors for the second consecutive week. Overall, the Women of Troy recorded a .214 hitting percentage while holding the Huskies to .131, spurring the team on to its first straight-sets victory over Washington since 2011.The balanced offensive effort also came with equally strong defense.  Leading the back row was junior libero Victoria Garrick, who had 13 digs alongside her eight assists.  Lanier and Meyer-Whalley also added 12 digs each. Though the Huskies out-blocked USC 11-5 on the day, the Women of Troy also had eight more digs as a team, recording 58 to Washington’s 50.Meyer-Whalley earned her fifth consecutive double-double this match, raising her career tally to 14, while Lanier’s 11 kills and 12 digs sealed the sophomore’s 20th double-double in Cardinal and Gold.The Trojans continue Pac-12 play on the road next weekend, facing Arizona State and Arizona. They will face the Wildcats first on Friday night before traveling to Tempe for ASU on Saturday.last_img read more

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How Google is making music with artificial intelligence

first_img Fred Bertsch google Q: What examples does Magenta learn from?A: We trained the NSynth algorithm, which uses neural networks to synthesize new sounds, on notes generated by different instruments. The SketchRNN algorithm was trained on millions of drawings from our Quick, Draw! game. Our most recent music algorithm, Performance RNN was trained on classical piano performances captured on a modern player piano [listen below]. I’d like musicians to be able to easily train models on their own musical creations, then have fun with the resulting music, further improving it. Sign up for our daily newsletter Get more great content like this delivered right to you! Country Can computers be creative? That’s a question bordering on the philosophical, but artificial intelligence (AI) can certainly make music and artwork that people find pleasing. Last year, Google launched Magenta, a research project aimed at pushing the limits of what AI can do in the arts. Science spoke with Douglas Eck, the team’s lead in San Francisco, California, about the past, present, and future of creative AI. This interview has been edited for brevity and clarity.Q: How does Magenta compose music?A: Learning is the key. We’re not spending any effort on classical AI approaches, which build intelligence using rules. We’ve tried lots of different machine-learning techniques, including recurrent neural networks, convolutional neural networks, variational methods, adversarial training methods, and reinforcement learning. Explaining all of those buzzwords is too much for a short answer. What I can say is that they’re all different techniques for learning by example to generate something new.  00:0000:0000:00 Country * Afghanistan Aland Islands Albania Algeria Andorra Angola Anguilla Antarctica Antigua and Barbuda Argentina Armenia Aruba Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium Belize Benin Bermuda Bhutan Bolivia, Plurinational State of Bonaire, Sint Eustatius and Saba Bosnia and Herzegovina Botswana Bouvet Island Brazil British Indian Ocean Territory Brunei Darussalam Bulgaria Burkina Faso Burundi Cambodia Cameroon Canada Cape Verde Cayman Islands Central African Republic Chad Chile China Christmas Island Cocos (Keeling) Islands Colombia Comoros Congo Congo, the Democratic Republic of the Cook Islands Costa Rica Cote d’Ivoire Croatia Cuba Curaçao Cyprus Czech Republic Denmark Djibouti Dominica Dominican Republic Ecuador Egypt El Salvador Equatorial Guinea Eritrea Estonia Ethiopia Falkland Islands (Malvinas) Faroe Islands Fiji Finland France French Guiana French Polynesia French Southern Territories Gabon Gambia Georgia Germany Ghana Gibraltar Greece Greenland Grenada Guadeloupe Guatemala Guernsey Guinea Guinea-Bissau Guyana Haiti Heard Island and McDonald Islands Holy See (Vatican City State) Honduras Hungary Iceland India Indonesia Iran, Islamic Republic of Iraq Ireland Isle of Man Israel Italy Jamaica Japan Jersey Jordan Kazakhstan Kenya Kiribati Korea, Democratic People’s Republic of Korea, Republic of Kuwait Kyrgyzstan Lao People’s Democratic Republic Latvia Lebanon Lesotho Liberia Libyan Arab Jamahiriya Liechtenstein Lithuania Luxembourg Macao Macedonia, the former Yugoslav Republic of Madagascar Malawi Malaysia Maldives Mali Malta Martinique Mauritania Mauritius Mayotte Mexico Moldova, Republic of Monaco Mongolia Montenegro Montserrat Morocco Mozambique Myanmar Namibia Nauru Nepal Netherlands New Caledonia New Zealand Nicaragua Niger Nigeria Niue Norfolk Island Norway Oman Pakistan Palestine Panama Papua New Guinea Paraguay Peru Philippines Pitcairn Poland Portugal Qatar Reunion Romania Russian Federation Rwanda Saint Barthélemy Saint Helena, Ascension and Tristan da Cunha Saint Kitts and Nevis Saint Lucia Saint Martin (French part) Saint Pierre and Miquelon Saint Vincent and the Grenadines Samoa San Marino Sao Tome and Principe Saudi Arabia Senegal Serbia Seychelles Sierra Leone Singapore Sint Maarten (Dutch part) Slovakia Slovenia Solomon Islands Somalia South Africa South Georgia and the South Sandwich Islands South Sudan Spain Sri Lanka Sudan Suriname Svalbard and Jan Mayen Swaziland Sweden Switzerland Syrian Arab Republic Taiwan Tajikistan Tanzania, United Republic of Thailand Timor-Leste Togo Tokelau Tonga Trinidad and Tobago Tunisia Turkey Turkmenistan Turks and Caicos Islands Tuvalu Uganda Ukraine United Arab Emirates United Kingdom United States Uruguay Uzbekistan Vanuatu Venezuela, Bolivarian Republic of Vietnam Virgin Islands, British Wallis and Futuna Western Sahara Yemen Zambia Zimbabwe How Google is making music with artificial intelligence Click to view the privacy policy. Required fields are indicated by an asterisk (*) Q: How has computer composition changed over the years?A: Currently the focus is on algorithms which learn by example, i.e., machine learning, instead of using hard-coded rules. I also think there’s been increased focus on using computers as assistants for human creativity rather than as a replacement technology, such as our work and Sony’s “Daddy’s Car” [a computer-composed song inspired by The Beatles and fleshed out by a human producer].Q: Do the results of computer-generated music ever surprise you?A: Yeah. All the time. I was really surprised at how expressive the short compositions were from Ian Simon and Sageev Oore’s recent Performance RNN algorithm. Because they trained on real performances captured in MIDI on Disklavier pianos, their model was able to generate sequences with realistic timing and dynamics.Q: What else is Magenta doing?A: We did a summer internship around joke telling, but we didn’t generate any funny jokes. We’re also working on image generation and drawing generation [see example below]. In the future, I’d like to look more at areas related to design. Can we provide tools for architects or web page creators?  Email A musician improvises alongside A.I. Duet, software developed in part by Google’s Magenta  By Matthew HutsonAug. 8, 2017 , 3:40 PM Magenta software can learn artistic styles from human paintings and apply them to new images. Q: How do you respond to art that you know comes from a computer?A: When I was on the computer science faculty at University of Montreal [in Canada], I heard some computer music by a music faculty member, Jean Piché. He’d written a program that could generate music somewhat like that of the jazz pianist Keith Jarrett. It wasn’t nearly as engaging as the real Keith Jarrett! But I still really enjoyed it, because programming the algorithm is itself a creative act. I think knowing Jean and attributing this cool program to him made me much more responsive than I would have been otherwise. Q: If abilities once thought to be uniquely human can be aped by an algorithm, should we think differently about them?A: I think differently about chess now that machines can play it well. But I don’t see that chess-playing computers have devalued the game. People still love to play! And computers have become great tools for learning chess. Furthermore, I think it’s interesting to compare and contrast how chess masters approach the game versus how computers solve the problem—visualization and experience versus brute-force search, for example.Q: How might people and machines collaborate to be more creative?A: I think it’s an iterative process. Every new technology that made a difference in art took some time to figure out. I love to think of Magenta like an electric guitar. Rickenbacker and Gibson electrified guitars with the purpose of being loud enough to compete with other instruments onstage. Jimi Hendrix and Joni Mitchell and Marc Ribot and St. Vincent and a thousand other guitarists who pushed the envelope on how this instrument can be played were all using the instrument the wrong way, some said—retuning, distorting, bending strings, playing upside-down, using effects pedals, etc. No matter how fast machine learning advances in terms of generative models, artists will work faster to push the boundaries of what’s possible there, too.last_img read more

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