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Canada-0-PHYSICIANS SURGEON OPTOMETRISTS 公司名录

企业名单和公司名单:
01 COMMUNIQUE LABORATORIES
公司地址:  1450 Meyerside Dr,MISSISSAUGA,ON,Canada
邮政编码:  L5T
电话号码:  9057958322
传真号码:  
免费电话号码:  
手机号码:  
网址:  
电子邮件:  
美国SIC代码:  0
美国的SIC目录:  Motorcycles & Motor Scooters-D
销售收入:  $1 to 2.5 million
员工人数:  1 to 4
信用报告:  Unknown
联系人:  

02 KIOSK PROMOTIONS
公司地址:  6551 No 3 Rd,RICHMOND,BC,Canada
邮政编码:  V7A
电话号码:  6042070477
传真号码:  6042738947
免费电话号码:  
手机号码:  
网址:  
电子邮件:  
美国SIC代码:  0
美国的SIC目录:  Womens Apparel-Retail
销售收入:  $2.5 to 5 million
员工人数:  20 to 49
信用报告:  Good
联系人:  

057305 NB LTD
公司地址:  3 Av Fallsview,SAINT JOHN,NB,Canada
邮政编码:  E2K
电话号码:  5066329626
传真号码:  
免费电话号码:  
手机号码:  
网址:  
电子邮件:  
美国SIC代码:  0
美国的SIC目录:  MASSAGE THERAPY & THERAPISTS
销售收入:  
员工人数:  
信用报告:  
联系人:  

1 FOR 1 PIZZA
公司地址:  911 Richmond Rd,OTTAWA,ON,Canada
邮政编码:  K2A
电话号码:  6137283100
传真号码:  
免费电话号码:  
手机号码:  
网址:  
电子邮件:  
美国SIC代码:  0
美国的SIC目录:  Restaurants
销售收入:  $500,000 to $1 million
员工人数:  10 to 19
信用报告:  Good
联系人:  

美国SIC代码:  0
美国的SIC目录:  Meat For Freezers
1 HOUR PHOTO RAPID IMAGES
公司地址:  South Common Mall,MISSISSAUGA,ON,Canada
邮政编码:  L4T
电话号码:  9058280144
传真号码:  
免费电话号码:  
手机号码:  
网址:  
电子邮件:  
美国SIC代码:  0
美国的SIC目录:  Leather Cleaning
销售收入:  Less than $500,000
员工人数:  5 to 9
信用报告:  Unknown
联系人:  

1 MARQUEE ENTERPRISES
公司地址:  640 Windmill Rd,DARTMOUTH,NS,Canada
邮政编码:  B3B
电话号码:  9024681630
传真号码:  
免费电话号码:  
手机号码:  
网址:  
电子邮件:  
美国SIC代码:  0
美国的SIC目录:  DIGITAL IMAGING SERVICE
销售收入:  
员工人数:  
信用报告:  
联系人:  

1 STEP STORAGE LTD
公司地址:  5051 Calder Crt,RICHMOND,BC,Canada
邮政编码:  V7C
电话号码:  6042040001
传真号码:  
免费电话号码:  
手机号码:  
网址:  
电子邮件:  
美国SIC代码:  0
美国的SIC目录:  
销售收入:  
员工人数:  
信用报告:  
联系人:  

1-800 GOT JUNK
公司地址:  2473 Sheffield Rd,ORLEANS,ON,Canada
邮政编码:  K1C
电话号码:  6138415954
传真号码:  
免费电话号码:  
手机号码:  
网址:  
电子邮件:  
美国SIC代码:  0
美国的SIC目录:  Freight-Forwarding
销售收入:  $500,000 to $1 million
员工人数:  5 to 9
信用报告:  Good
联系人:  

1-888-ROSE INC
公司地址:  8407 Argyll Rd NW,EDMONTON,AB,Canada
邮政编码:  T6C
电话号码:  7804392848
传真号码:  7804524980
免费电话号码:  
手机号码:  
网址:  
电子邮件:  
美国SIC代码:  0
美国的SIC目录:  Environmental & Ecological Ser
销售收入:  $1 to 2.5 million
员工人数:  5 to 9
信用报告:  Unknown
联系人:  

10 FRIENDS DINER
公司地址:  4141 Tecumseh Rd E,WINDSOR,ON,Canada
邮政编码:  N8W
电话号码:  5192543000
传真号码:  
免费电话号码:  
手机号码:  
网址:  
电子邮件:  
美国SIC代码:  0
美国的SIC目录:  
销售收入:  
员工人数:  
信用报告:  
联系人:  

10-2-10 CONVENIENCE
公司地址:  521 20th St W,SASKATOON,SK,Canada
邮政编码:  S7M
电话号码:  3069558893
传真号码:  
免费电话号码:  
手机号码:  
网址:  
电子邮件:  
美国SIC代码:  0
美国的SIC目录:  
销售收入:  
员工人数:  
信用报告:  
联系人:  

10/10 MARKETING INC
公司地址:  170 Batoche Cres,SASKATOON,SK,Canada
邮政编码:  S7M
电话号码:  3066513200
传真号码:  
免费电话号码:  
手机号码:  
网址:  
电子邮件:  
美国SIC代码:  0
美国的SIC目录:  Dancing Instruction
销售收入:  Less than $500,000
员工人数:  1 to 4
信用报告:  Very Good
联系人:  

Show 1-13 record,Total 600 record
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公司新闻:
  • Massachusetts Institute of Technology - MIT News
    Teaching AI models the broad strokes to sketch more like humans do SketchAgent, a drawing system developed by MIT CSAIL researchers, sketches up concepts stroke-by-stroke, teaching language models to visually express concepts on their own and collaborate with humans
  • How we really judge AI | MIT News | Massachusetts Institute of Technology
    For instance, AI appreciation is more pronounced for tangible robots than for intangible algorithms Economic context also matters In countries with lower unemployment, AI appreciation is more pronounced “It makes intuitive sense,” Lu says “If you worry about being replaced by AI, you’re less likely to embrace it ”
  • Explained: Generative AI’s environmental impact - MIT News
    Plus, generative AI models have an especially short shelf-life, driven by rising demand for new AI applications Companies release new models every few weeks, so the energy used to train prior versions goes to waste, Bashir adds New models often consume more energy for training, since they usually have more parameters than their predecessors
  • Algorithms and AI for a better world - MIT News
    A good example of Raghavan’s intention can be found in his exploration of the use AI in hiring Raghavan says, “It’s hard to argue that hiring practices historically have been particularly good or worth preserving, and tools that learn from historical data inherit all of the biases and mistakes that humans have made in the past ”
  • MIT researchers introduce generative AI for databases
    Researchers from MIT and elsewhere developed an easy-to-use tool that enables someone to perform complicated statistical analyses on tabular data using just a few keystrokes Their method combines probabilistic AI models with the programming language SQL to provide faster and more accurate results than other methods
  • Introducing the MIT Generative AI Impact Consortium
    The MIT Generative AI Impact Consortium is a collaboration between MIT, founding member companies, and researchers across disciplines who aim to develop open-source generative AI solutions, accelerating innovations in education, research, and industry
  • Explained: Generative AI | MIT News | Massachusetts Institute of Technology
    Before the generative AI boom of the past few years, when people talked about AI, typically they were talking about machine-learning models that can learn to make a prediction based on data For instance, such models are trained, using millions of examples, to predict whether a certain X-ray shows signs of a tumor or if a particular borrower is
  • MIT researchers develop an efficient way to train more reliable AI . . .
    Reinforcement learning models, which underlie these AI decision-making systems, still often fail when faced with even small variations in the tasks they are trained to perform In the case of traffic, a model might struggle to control a set of intersections with different speed limits, numbers of lanes, or traffic patterns
  • “Periodic table of machine learning” could fuel AI discovery
    The new framework sheds light on how scientists could fuse strategies from different methods to improve existing AI models or come up with new ones For instance, the researchers used their framework to combine elements of two different algorithms to create a new image-classification algorithm that performed 8 percent better than current state




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