The document outlines recent advancements in artificial intelligence (AI) across various fields including photorealistic content generation, natural language processing, speech recognition, and AI in healthcare. It highlights notable projects like DeepMind's AlphaFold, OpenAI's GPT-2, and the growth of smart speakers, forecasting a significant increase in AI applications and cloud-based services. Additionally, it discusses the impact of edge AI and large-scale real-life applications from companies like Alibaba and Amazon.

1. Grigory Sapunov
Atlas / Moscow / 26.04.2019
gs@inten.to
AI: last year progress

2. 1. Photorealistic content generation

3. Deep Video Portraits
https://web.stanford.edu/~zollhoef/papers/SG2018_DeepVideo/page.html
https://techcrunch.com/2018/06/04/forget-deepfakes-deep-video-portraits-are-way-better-and-worse/
“We present a novel approach that enables photo-realistic re-animation of portrait videos using
only an input video. In contrast to existing approaches that are restricted to manipulations of
facial expressions only, we are the first to transfer the full 3D head position, head rotation, face
expression, eye gaze, and eye blinking from a source actor to a portrait video of a target
actor.”

4. GAN rapid evolution
The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation
https://arxiv.org/abs/1802.07228

5. High-resolution photorealistic video-to-video transl.
https://github.com/NVIDIA/vid2vid
Video-to-Video Synthesis: https://arxiv.org/abs/1808.06601

9. Example: BigGAN
Large Scale GAN Training for High Fidelity Natural Image Synthesis,
https://arxiv.org/abs/1809.11096

10. Example: Generating images by GAN
http://www.whichfaceisreal.com/index.php

11. Example: Face editing by GAN
https://twitter.com/reza_zadeh/status/1098513886456598529

12. Example: Face editing by GAN
SC-FEGAN: Face Editing Generative Adversarial Network with User's Sketch and Color,
https://arxiv.org/abs/1902.06838, https://github.com/JoYoungjoo/SC-FEGAN

13. Example: GauGAN
https://blogs.nvidia.com/blog/2019/03/18/gaugan-photorealistic-landscapes-nvidia-research/
Semantic Image Synthesis with Spatially-Adaptive Normalization, https://arxiv.org/abs/1903.07291

14. Plus: NVIDIA Real-Time Ray Tracing
https://developer.nvidia.com/rtx

15. NVIDIA DRIVE Constellation AV Simulator
https://www.nvidia.com/en-us/self-driving-cars/drive-constellation/

16. 2. Natural Language Processing
(NLP)

17. AI2’s ELMo: NLP's ImageNet moment has arrived (*1st
time)
https://thegradient.pub/nlp-imagenet/

18. Google’s BERT
A Conversational Question Answering Challenge: https://stanfordnlp.github.io/coqa/

19. OpenAI’s GPT-2
https://blog.openai.com/better-language-models/

20. 3. Speech & Sound

21. Case: Google Assistant / Screen Calls

22. Smart Speakers
DELOITTE Global predicts that the industry
for smart speakers—internet-connected
speakers with integrated digital voice
assistants—will be worth US$7 billion in
2019, selling 164 million units at an average
selling price of US$43.1 We expect 2018 sales of 98 million units at an average of
US$44 each, for a total industry revenue of US$4.3 billion. This 63 percent growth
rate would make smart speakers the fastest-growing connected device category
worldwide in 2019, and lead to an installed base of more than 250 million units by
year-end.
https://www2.deloitte.com/insights/us/en/industry/technology/technology-media-and-telecom-predictions/smart-speaker-voice-computing.html

23. New approaches: 2.5D sound
Converting monaural audio into binaural audio by leveraging video
2.5D Visual Sound, https://arxiv.org/abs/1812.04204
https://www.youtube.com/watch?v=t_7qpPOmsME

24. 4. AI Strategies

25. National and International AI strategies
https://futureoflife.org/ai-policy/

26. National and International AI strategies
https://futureoflife.org/national-international-ai-strategies

27. National and International AI strategies
https://futureoflife.org/national-international-ai-strategies

28. 5. Turing Award, the Nobel Prize of
computing

29. Fathers of the DL Revolution receive ACM Turing Award

30. 6. Artificial General Intelligence
(AGI)

31. Still no AGI

32. 7. Games

33. AlphaGo Lee: Computer-Human 4:1

34. AlphaGo Zero

35. AlphaZero

36. AlphaZero
https://deepmind.com/blog/alphazero-shedding-new-light-grand-games-chess-shogi-and-go/

37. AlphaZero
http://science.sciencemag.org/content/362/6419/1087
“AlphaZero shows us that machines can be the experts,
not merely expert tools. Explainability is still an issue —
it's not going to put chess coaches out of business just
yet. But the knowledge it generates is information
we can all learn from. Alpha-Zero is surpassing us in a
profound and useful way, a model that may be
duplicated on any other task or field where virtual
knowledge can be generated.”
-- Garry Kasparov
Chess, a Drosophila of reasoning,
Science 07 Dec 2018

38. Dota 2
https://openai.com/five/

39. Dota 2: OpenAI Five
(Jun 25, 2018) Our team of five neural networks, OpenAI Five, has started to
defeat amateur human teams at Dota 2.
(Aug 5, 2018) OpenAI Five won a best-of-three against a team of 99.95th
percentile Dota players. The human team won game three after the audience
adversarially selected Five’s heroes.
(Aug 23, 2018) OpenAI Five lost two games against top Dota 2 players at
The International in Vancouver this week, maintaining a good chance of winning
for the first 20-35 minutes of both games.
(Apr 13, 2019) In a series of live competitions between the reigning Dota 2
world champion team OG and the five-bot team OpenAI Five, the AI won two
matches back-to-back, settling the best-of-three tournament.
https://blog.openai.com/openai-five/

40. StarCraft: AlphaStar
https://deepmind.com/blog/alphastar-mastering-real-time-strategy-game-starcraft-ii/

41. AlphaStar vs. Humans: 10-1
https://www.youtube.com/watch?v=DMXvkbAtHNY
https://www.engadget.com/2019/01/24/deepmind-ai-starcraft-ii-demonstration-tlo-mana/
“The AI agent, named AlphaStar, managed to pick up 10
wins against StarCraft II pros TLO and MaNa in two separate
five-game series that originally took place back in December.
After racking up 10 straight losses, the pros finally scored a
win against the AI when MaNa took on AlphaStar in a live
match streamed by Blizzard and DeepMind.”

42. AlphaGo approach in other domains
Learning to Plan Chemical Syntheses
https://arxiv.org/abs/1708.04202

43. 8. Medicine & Biology

44. DeepMind: AlphaFold
https://deepmind.com/blog/alphafold/
Predicting the 3D structure of a protein based solely on its genetic sequence.

45. DeepMind on AlphaFold
https://twitter.com/demishassabis/status/1069414015607152640

46. Predicting eye disease with Moorfields Eye Hospital
https://deepmind.com/blog/predicting-eye-disease-moorfields/
In August, we announced the first stage of our joint
research partnership with Moorfields Eye Hospital, which
showed how AI could match world-leading doctors at
recommending the correct course of treatment for
over 50 eye diseases, and also explain how it arrives at
its recommendations.
Now we’re excited to start working on the next research
challenge – whether we can help clinicians predict eye
diseases before symptoms set in.

47. Clara AI lets every radiologist teach their own AI
https://blogs.nvidia.com/blog/2019/03/18/clara-ai-gtc/
Clara AI, a toolkit that includes 13 state-of-the-art classification and segmentation AIs, and software tools
built for radiologists. Performance Speedup - Achieve 4X-10X speedup compared to manual editing
depending on the organ being segmented.

48. Medicine in the digital age
https://www.nature.com/nm/articles?type=perspective

49. AI in healthcare
https://www.nature.com/nm/articles?type=perspective

50. https://www.nature.com/articles/s41591-018-0300-7

51. https://www.nature.com/articles/s41591-018-0316-z

52. https://www.nature.com/articles/s41591-018-0316-z

53. https://www.nature.com/articles/s41591-018-0316-z

54. https://www.nature.com/articles/nmeth.4658

55. https://www.nature.com/articles/s41591-018-0300-7

56. https://www.nature.com/articles/s41591-018-0300-7

57. https://www.nature.com/articles/s41591-018-0300-7

58. 9. Large-scale real-life applications

59. Alibaba Hangzhou ET City Brain 2.0
https://www.alibabacloud.com/et/city
https://www.alizila.com/alibaba-cloud-launched-city-brain-2-0-hangzhou/
https://technode.com/2018/09/19/alibaba-city-brain/
(Sep 19, 2018) First launched in September 2016, City Brain is mainly used to improve traffic flows,
make live traffic predictions, and detect traffic incidents using data from video footage, traffic bureaus,
and public transportation systems. After two years, Hangzhou, the first city to embrace the system,
dropped from the 5th to the 57th spot on the list for China’s most congested cities, according to
the company.
The latest version is expected to monitor and control the city’s traffic at a larger scale and with more
accuracy. Hangzhou City Brain 2.0 now covers a core area of 42 square kilometers in downtown
Hangzhou, while the traffic violations are reported with 95% accuracy. The system has over 110
autonomous alert capabilities and 1300 traffic signals that are controlled by AI, according to Jing Zhi,
deputy chief of the Zhejiang Provincial Public Security Department. Over 200 traffic policemen are
available through the platform to attend to traffic emergencies.

62. Google DeepMind: ML in data centers
Safety-first AI for autonomous data centre cooling and industrial control
https://deepmind.com/blog/safety-first-ai-autonomous-data-centre-cooling-and-industrial-control/
Whereas our original recommendation
system had operators vetting and
implementing actions, our new AI
control system directly implements the
actions.
Despite being in place for only a matter
of months, the system is already
delivering consistent energy savings
of around 30 percent on average,
with further expected improvements.

63. DeepMind: Optimizing wind power generation
https://deepmind.com/blog/machine-learning-can-boost-value-wind-energy/

64. Amazon Go
https://www.techradar.com/news/amazon-is-planning-to-open-bigger-automated-stores
(Dec, 2018) Amazon is testing larger version of its
automated Amazon Go brick-and-mortar stores.
Existing Amazon Go outlets are only the size of a
small convenience store. Larger stores with more
diverse products mean new challenges, including
managing far more products, and dealing with larger
spaces that are harder to monitor.
The sources claim that Amazon is planning to open as many as 3,000 physical stores by 2021, enabling
it to better compete with big supermarket chains like Walmart

65. Amazon Scout
https://blog.aboutamazon.com/transportation/meet-scout
(Jan 23, 2019) A fully-electric delivery system – Amazon
Scout – designed to safely get packages to customers using
autonomous delivery devices. These devices were created
by Amazon, are the size of a small cooler, and roll along
sidewalks at a walking pace. Starting today, these devices
will begin delivering packages to customers in a
neighborhood in Snohomish County, Washington.

66. FedEx SameDay Bot
https://about.van.fedex.com/newsroom/thefuturefedex/
(Feb 27, 2019) An autonomous delivery device designed to help retailers make
same-day and last-mile deliveries to their customers.
On average, more than 60 percent of merchants’ customers live within three miles
of a store location, demonstrating the opportunity for on-demand, hyper-local
delivery.
FedEx plans to test the bot this summer in select markets, including Memphis,
Tenn., pending final city approvals.

67. ● 31,000K orders delivered successfully
● 150 Kiwibots roaming around
● https://www.kiwicampus.com/
(Feb 7, 2019) “By breaking the 500 orders in a day mark, we will set a
world record and we will gain those resources that will allow us to keep
working for a stronger Berkeley, the place that gave us everything.”
https://medium.com/kiwicampus/kiwis-world-record-beec49f26a07
KiwiBot

68. Tesla: Autopilot reaches 1 billion miles
https://deeplearning.mit.edu/

69. 10. Cloud AI

70. Cloud: The democratization of AI
Deloitte also predicts that in 2019 companies will further accelerate usage of cloud-based artificial
intelligence (AI) software and services. Among companies using AI, 70 percent will obtain AI
capabilities through cloud-based enterprise software, 65 percent will create AI applications
using cloud-based development services, and by 2020, the penetration rate of enterprise
software with AI built in, and cloud-based AI development services will reach an estimated 87 and 83
percent respectively.
“So far, AI’s initial benefits have been predominantly accrued by ‘tech giants’ with extensive financial
resources, strong IT infrastructure, and highly-specialized human capital,” says Paul Sallomi, Deloitte
Global Technology, Media & Telecommunications industry leader. “However, the cloud will power
increased efficiencies and better returns on investment, and we expect these benefits to rapidly
extend beyond AI’s pioneers to the wider enterprise.”
Deloitte Global TMT Predictions 2019
https://www2.deloitte.com/global/en/pages/about-deloitte/press-releases/deloitte-global-tmt-predictions-2019.html

71. Example: NLP cloud APIs / 60+ APIs

72. Example: Google AutoML / customized models
https://cloud.google.com/automl/

73. 11. Edge AI

74. AI at the edge
● NVidia Jetson TK1/TX1/TX2/Xavier/Nano
○ 192/256/256/512/128 CUDA Cores
○ 4/4/6/8/4-Core ARM CPU, 2/4/8/16/4 Gb Mem
● Tablets, Smartphones
○ Qualcomm Snapdragon 845/855, Apple A11/12/Bionic, Huawei Kirin 970/980
● Raspberry Pi 3 (1.2 GHz 4-core)
● Movidius Neural Compute Stick, Stick 2
● Google Edge TPU

75. (Aug 31, 2018) World's first 7nm process mobile AI chipset
Kirin 980 can quickly adapt to AI scenes such as face recognition,
object recognition, object detection, image segmentation and
intelligent translation with the power of a dual-core NPU achieving
4500 images per minute which is an improved 120% recognition speed. So
whether it's dancing to a fast song or quickly running in front of the camera, the
Kirin 980 can focus on the joints and lines of the human body in real time. The
powerful object detection capabilities can also accurately identify a variety of
objects. In comparison to the Kirin 970, the Kirin 980 is an impressive leap from
image recognition to object detection. The Kirin 980 sets the foundation for future
AI capabilities by providing complete framework support and rich tool keys for
App developers.
https://consumer.huawei.com/en/campaign/kirin980/
Mobile AI: Huawei Kirin 980 (NPU)

76. (Sep 12, 2018) Apple A12 Bionic
The A12 includes dedicated neural network hardware that
Apple calls a "Next-generation Neural Engine."
This neural network hardware has eight cores and can perform
up to 5 trillion 8-bit operations per second.
Unlike the A11's Neural Engine, third party apps can access the A12's Neural
Engine.
https://en.wikipedia.org/wiki/Apple_A12
Mobile AI: Apple A12 Neural Engine

77. (Nov 14, 2018) Samsung Brings On-device AI Processing for
Premium Mobile Devices with Exynos 9 Series 9820 Processor
The Exynos 9820 is an intelligent powerhouse with a separate
hardware AI-accelerator, or NPU, which performs AI tasks around seven times
faster than the predecessor. With the NPU, AI-related processing can be
carried out directly on the device rather than sending the task to a server,
providing faster performance as well as better security of personal
information. The NPU will enable a variety of new experiences such as instantly
adjusting camera settings for a shot based on the surroundings or recognizing
objects to provide information in augmented or virtual reality (AR or VR) settings.
https://news.samsung.com/global/samsung-brings-on-device-ai-processing-for-premium-mobile-devices-with-exynos-9-seri
es-9820-processor
https://www.samsung.com/semiconductor/minisite/exynos/products/mobileprocessor/exynos-9-series-9820/
Mobile AI: Samsung (NPU)

78. (Dec 5, 2018) Qualcomm Announces New Flagship
Snapdragon 855 Mobile Platform - A New Decade of 5G, AI,
and XR
The Hexagon 690 Digital Signal Processor (DSP) is a more powerful processor for
AI work and the fourth-generation AI engine is capable of 7 trillion operations per
second and offering three times improvement in performance over the previous
generation and, claims Qualcomm, twice the AI performance of “7nm smartphone
competitors” – it’s particularly referring to Huawei’s Kirin 980 there.
https://www.qualcomm.com/news/releases/2018/12/05/qualcomm-announces-new-flagship-snapdragon-855-mobile-platfor
m-new-decade
https://www.pocket-lint.com/phones/news/qualcomm/146477-qualcomm-snapdragon-855
https://www.qualcomm.com/products/snapdragon-855-mobile-platform
Mobile AI: Qualcomm Snapdragon 855

79. (Nov 14, 2018) Neural Compute Stick 2
The new, improved Intel Neural Compute Stick 2 (NCS 2)
features Intel’s latest high-performance vision processing
unit: the Intel Movidius Myriad X VPU. With more compute cores and a dedicated
hardware accelerator for deep neural network inference, the Intel NCS 2 delivers
up to eight times the performance boost compared to the previous generation Intel
Movidius Neural Compute Stick (NCS).
https://software.intel.com/en-us/neural-compute-stick
AI at the Edge: Intel/Movidius

80. AI at the Edge: Google Edge TPU
● (July 2018) Edge TPU is Google’s purpose-built ASIC designed to run AI
at the edge. It delivers high performance in a small physical and power
footprint, enabling the deployment of high-accuracy AI at the edge.
https://cloud.google.com/edge-tpu/

81. AI at the Edge: Jetson Nano
● (Mar 18, 2019) AI computer that delivers 472 GFLOPS of compute
performance for running modern AI workloads.
● Highly power-efficient, consuming as little as 5 watts.
● $99 devkit for developers, makers and enthusiasts;
$129 production-ready module for companies looking to create
mass-market edge systems.
https://nvidianews.nvidia.com/news/nvidia-announces-jetson-nano-99-tiny-yet-mighty-nvidia-cuda-x-ai-computer-that-runs-all-ai-models

82. https://ru.linkedin.com/in/grigorysapunov
gs@inten.to
Thanks!