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June 2019 |
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Introducing the NEW 9th Gen Intel® Core™ desktop processors - the most powerful generation of Intel® Core™ desktop processors. Whether you are a gamer looking for a fantastic in-game experience with the performance headroom for smooth live streaming and seamless highlights recording or you are a creator that is ready to do more creating and sharing, less time waiting, this new generation of processors is ready to take you to that new level.
A New Level of Performance
The 9th Gen Intel® Core™ processor takes mainstream desktop PC performance to a whole new level. At the top of the stack, our mainstream flagship, the new i9-9900K. The first Intel® Core™ i9 desktop processor for the mainstream users. Best in class, the i9-9900K with 16MB of cache and Intel® Turbo Boost 2.0 technology cranks maximum turbo frequency up to blazing 5.0 GHz. Throw in high performing 16-way multitasking support powered by 8 cores with Intel® Hyper-Threading Technology (Intel® HT Technology) to conquer the most demanding workloads. Want to reach for even greater levels of performance? — Overclock confidently with new and enhanced features like Solder Thermal Interface Material (STIM) and improved overclocking customizations to tweak the processor performance to its unleashed potential.
The NEW 9th Generation of Intel® Core™ Desktop Processor Delivers:
- A range of processors including the first unlocked Intel® Core™ i9 mainstream desktop processor.
- Data acceleration when paired with Intel® Optane™ memory to retrieve that data you use the most for fast system responsiveness.
- DDR4 RAM memory technology support, which allows systems to have up to 64 GB of memory and up to 2666 MT/s memory transfer speeds.
- Intel® Z390 chipset support which includes unprecedented connectivity to all of your devices with integrated USB 3.1 Gen 2, Intel® Wireless-AC, and support for Gigabit Wi-Fi speed.
- Compatible with Intel® 300 series chipset.
Game on a Whole New Level
Game, Record, Stream without compromise on a system powered by a 9th Generation Intel® Core™ i9 processor.
Utilize Intel® Quick Sync Video technology to live-stream, capture, and multitask without interruption. Power up and customize your gaming rig with up to 40 platform PCIe lanes giving you the outstanding flexibility.
Pair it with Intel® Optane™ memory technology to accelerate the loading and launching of the games you play the most.
Create Without Limits
Unlock your creative potential with the power you need to create, edit, and share. Let your creativity flow as the 9th Generation Intel® Core™ processor renders and encodes in the background so you don’t miss a beat. Minimize the wait time between inspiration and creation with Intel® Optane™ memory accelerating the loading of your most used applications.
Ultra-High Definition Entertainment
Desktop computers based on the 9th Generation Intel® Core™ processors integrate advanced media technologies that bring premium, high-quality content to your desktop, including:
HEVC 10-bit encode/decode, VP9 10-bit decode:
- Delivering smooth streaming of premium 4K UHD entertainment to your PC from leading online providers.
- Providing full-size, screen-immersive viewing experiences with 4K video and 360-degree viewing.
High Dynamic Range (HDR) and Rec. 2020 (Wide Color Gamut) for life-like luminesces to provide enhanced image and video viewing experiences.
Hardware Based Security
9th Generation Intel® Core™ processors integrate hardware level technologies that help strengthen the protection of your enabled security software. Hardware-based security helps you experience online and offline activities with added peace of mind, enabled by features that include:
Intel® Software Guard Extensions (Intel® SGX) to help applications protect your system and your data.
Intel® BIOS Guard and Intel® Boot Guard to help protect your system during startup.
Scalable Portfolio of Processors
A 9th Generation Intel® Core™ processor is a great investment in your desktop experiences — whether for gaming, creating, entertainment, or general purpose computing — wherever your life takes you.
Step Up to the Next Level with 9th Gen Intel® Core™ Desktop Processors
9th Gen is the most powerful generation of Intel® Core™ desktop processors, with features and enhancements to evoke excitement in what you love to do. Step up to a 9th Gen Intel® Core™ processor-powered PC and experience the difference.
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| Model Number |
Cores |
Frequency |
Turbo-Quad |
L3 Cache |
GPU Model |
GPU Frequency |
TDP |
Socket |
Release Date |
Core i3
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| Core i3-9100 |
4(4 Threads)
|
3.6 GHz |
4.2 GHz
|
6 MB |
HD 630 |
350-1100 MHz |
65 W |
LGA 1151 |
Q2' 2019 |
Core i5
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| Core i5-9400 |
6(6 Threads)
|
2.9 GHz |
4.1 GHz
|
9 MB |
HD 630 |
350-1050 MHz |
65 W |
LGA 1151 |
Q1' 2019 |
| Core i5-9600 |
6(6 Threads)
|
3.1 GHz |
4.6 GHz
|
9 MB |
HD 630 |
350-1150 MHz |
65 W |
LGA 1151 |
Q2' 2019 |
| Core i5-9600K |
6(6 Threads)
|
3.7 GHz |
4.6 GHz
|
9 MB |
HD 630 |
350-1150 MHz |
95 W |
LGA 1151 |
Q4' 2018 |
Core i7
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| Core i7-9700 |
8(8 Threads)
|
3.0 GHz |
4.7 GHz
|
12 MB |
HD 630 |
350-1200 MHz |
65 W |
LGA 1151 |
Q2' 2019 |
| Core i7-9700K |
8(8 Threads)
|
3.6 GHz |
4.9 GHz
|
12 MB |
HD 630 |
350-1200 MHz |
95 W |
LGA 1151 |
Q4' 2018 |
Core i9
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| Core i9-9900 |
8(16 Threads)
|
3.1 GHz |
5.0 GHz
|
16 MB |
HD 630 |
350-1200 MHz |
65 W |
LGA 1151 |
Q2' 2019 |
| Core i9-9900K |
8(16 Threads)
|
3.6 GHz |
5.0 GHz
|
16 MB |
HD 630 |
350-1200 MHz |
95 W |
LGA 1151 |
Q4' 2018 |
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June 2019 |
Example 1- Curation of Internet’s Contents
* As we accumulate more and more information, how do we curate the content as to correctly distinguish truth from fiction? The task of curating the Internet’s contents is huge. We will need widespread collaboration some of it with automated tools based on AI and Machine Learning. Source: ACM printed edition of Communications for 2019-02.
Example 2- Cambridge on Brawls
* Researchers at the University of Cambridge in the U.K. working with colleagues at the Indian Institute of Science, Bangalore and India's National Institute of Technology, Warangal, have used deep learning to develop a drone surveillance system that automatically detects small groups of people fighting each other. Source:
https://spectrum.ieee.org/tech-talk/robotics/artificial-intelligence/ai-drone-learns-to-detect-brawls
Example 3- Detect Fake News
* Source: https://news.umich.edu/fake-news-detector-algorithm-works-better-than-a-human/. Researchers at the University of Michigan have developed an algorithm-based system that identifies linguistic cues in fake news stories. The researchers found the system successfully identified fake stories up to 76% of the time, surpassing the human success rate of 70%.
Example 4- Detect Fake Photo
* A new system developed by researchers at the University of California, Berkeley and Carnegie Mellon University, can identify inconsistencies in doctored images. The metadata of 400,000 Flickr photos was used to teach the system to distinguish imagery from two different sources. The researchers say digital imagery must be determined by the particular technologies or processes behind it, and the effects of those processes are generally consistent across the whole image. If the system can learn which devices produce which aspects of an image, it can ascertain whether an image has been altered by combining data from multiple devices.
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June 2019 |
Example 1- Curation of Internet’s Contents
* As we accumulate more and more information, how do we curate the content as to correctly distinguish truth from fiction? The task of curating the Internet’s contents is huge. We will need widespread collaboration some of it with automated tools based on AI and Machine Learning. Source: ACM printed edition of Communications for 2019-02.
Example 2- Cambridge on Brawls
* Researchers at the University of Cambridge in the U.K. working with colleagues at the Indian Institute of Science, Bangalore and India's National Institute of Technology, Warangal, have used deep learning to develop a drone surveillance system that automatically detects small groups of people fighting each other. Source:
https://spectrum.ieee.org/tech-talk/robotics/artificial-intelligence/ai-drone-learns-to-detect-brawls
Example 3- Detect Fake News
* Source: https://news.umich.edu/fake-news-detector-algorithm-works-better-than-a-human/. Researchers at the University of Michigan have developed an algorithm-based system that identifies linguistic cues in fake news stories. The researchers found the system successfully identified fake stories up to 76% of the time, surpassing the human success rate of 70%.
Example 4- Detect Fake Photo
* A new system developed by researchers at the University of California, Berkeley and Carnegie Mellon University, can identify inconsistencies in doctored images. The metadata of 400,000 Flickr photos was used to teach the system to distinguish imagery from two different sources. The researchers say digital imagery must be determined by the particular technologies or processes behind it, and the effects of those processes are generally consistent across the whole image. If the system can learn which devices produce which aspects of an image, it can ascertain whether an image has been altered by combining data from multiple devices.
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June 2019 |
Image Captioning Development Roadmap for 2019 – 2020
The immediate release in 2019-06 for Sampling is a model trained by Yueyuan up to 2018-06. The model was trained with nearly 100,000 images from Microsoft COCO dataset and reached a BLEU1 score of 0.651. The sampler for our peers consists of 100 images only and it is strictly not for commercial use. When the model is executed, it will create the captions of 10 images and display the captions and images for appraisal. The computer runtime should be in seconds. We will see that some captions are good while some are lousy- it is the state of the model.
The next Sampling release will have 2 different types of improvement. The first is that our peers are given the option of supplying up to 10 images for testing. Obviously some input data conditioning processing is required and this will take extra time. If the peer-supplied images have contents and styles different to the 100,000 images used for training, the captions are guaranteed to be poor as a reflection of the poor adaptability of the model to unseen images.
The second approach is an improved model with a peak BLEU1 score of close to 0.700. This model will obviously produce captions that are more sensible and less absurd.
In early 2020, the model will be trained with video surveillance footage so that it can interpret footage for property owners. However, this model will stay in the sampling stage and will not be mature enough for commercial deployment.
Two further streams of exploration not directly related to the above model are in progress. One stream deals with natural language processing. The other stream deals with physics assisted machine learning method. They are in the domain of academic exploration.
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June 2019 |
Image Captioning Development Roadmap for 2019 – 2020
The immediate release in 2019-06 for Sampling is a model trained by Yueyuan up to 2018-06. The model was trained with nearly 100,000 images from Microsoft COCO dataset and reached a BLEU1 score of 0.651. The sampler for our peers consists of 100 images only and it is strictly not for commercial use. When the model is executed, it will create the captions of 10 images and display the captions and images for appraisal. The computer runtime should be in seconds. We will see that some captions are good while some are lousy- it is the state of the model.
The next Sampling release will have 2 different types of improvement. The first is that our peers are given the option of supplying up to 10 images for testing. Obviously some input data conditioning processing is required and this will take extra time. If the peer-supplied images have contents and styles different to the 100,000 images used for training, the captions are guaranteed to be poor as a reflection of the poor adaptability of the model to unseen images.
The second approach is an improved model with a peak BLEU1 score of close to 0.700. This model will obviously produce captions that are more sensible and less absurd.
In early 2020, the model will be trained with video surveillance footage so that it can interpret footage for property owners. However, this model will stay in the sampling stage and will not be mature enough for commercial deployment.
Two further streams of exploration not directly related to the above model are in progress. One stream deals with natural language processing. The other stream deals with physics assisted machine learning method. They are in the domain of academic exploration.
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