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postolo · 6 years ago

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The Next Storm of Innovation in Digital Technologies in 2019: Challenge to IP Law

“Digital technologies are doing for human brainpower what the steam engine and related technologies did for human muscle power during the Industrial Revolution. They are allowing us to overcome many limitations rapidly and to open up new frontiers with unprecedented speed. It is a very big deal. But how exactly it will play out is uncertain.”

— Andrew McAfee

What are the Major Trends in Digital Technology (DT)

Due to the ripening of digital technologies, the society en bloc is undergoing a fast and radical transformation. To add to the increased demand from customers, companies are facing ever tougher competition due to globalisation and putting pressure to go digital before others do, seeking to survive and attain competitive advantages.

Hence, in recent years “born digital” pioneers (e.g., Amazon, Facebook and Google) have grown into powerful behemoths, while companies that long dominated their industries found their traditional value proposition under threat.[1]

Further to be added that every computing device [which has five basic components: (a) integrated circuits; (b) memory; (c) network systems; (d) software applications; and (e) sensors] is undergoing changes which humans cannot absorb. The biggest concern is what happens next? How could we legislate technology, we neither understand nor can predict its legal application/misapplication?

What will the Digital Technology Innovation Ecosystem Look Like in the Next Ten Years

In the impending ten years, the computer will eventually disappear, and will be everywhere but invisible (IOT). Music was the first industry to be digitised. Now it is media. Tomorrow, it is education, banking, medicine and transportation, etc. The table below explains the scenario is as follows:

Mature Emerging Futuristic

(i) Enterprise systems

(ii) Internet

(iii) Social Media and digital platforms

(iv) Mobile endpoint devices and Apps

(i) Cloud computing

(ii) Big data analytics

(iii) 3D printing/additive manufacturing

(iv) Algorithmic automation

(v) Sensors and the internet of things

(vi) Driverless vehicles and autonomous things

(i) Commercial drones

(ii) Artificial intelligence and cognitive computing

(iii) Blockchain, smart contracts

(iv) Conversational computing

(v) Virtual assistance

(vi) Virtual reality and augmented reality

(vii) Social robotics

(viii) Quantum computing

(ix) Human augmentation/brain-computer interfaces

Big Data: The New Gold Mine

Big data relates to large data. Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualisation, querying, updating, privacy and data source. Currently, the term “big data” tends to refer to the use of predictive analytics, user behaviour analytics, or certain other advanced data analytics methods that extract value from data.

Analysis of data sets can find new correlations to spot business trends, prevent diseases, combat crime and so on. Researchers, scientists, business executives, practitioners of medicine, and governments alike regularly need to mine and understand large data sets in areas including urban informatics and business informatics.

Challenges to Intellectual Property (IP) Law in “DT” Innovation

3D printing—3D printing could be a problem for patent-holders as its enforcement will be hard due to dispersed infringers. Only by simply removing the mark the 3D printing could overcome trade mark or trade dress. The jurisprudence is not conventional as case laws and legislation needs to be developed to manage 3D products/services. Moreover, the copyright system itself is not ready to respond to the challenges posed by DT acceleration. Also, patent law doctrines will be disrupted and may need to undergo certain legislative changes.

Artificial Intelligence (AI)

Businesses are increasingly interested in protecting their investments in the development of AI. Due to low cost, high-capacity storage and computing power, and the ubiquity of sensors that capture data of all types, companies are adding AI features to existing products and creating entirely new product offerings based on AI.

The world of “big data” has created both the availability of robust training sets used to develop AI technology and a need for technology that can process and filter large volumes of data for business applications. Recognising the need to protect the value of their investment in AI, companies are increasingly securing IP protection. The Patent and Trade Mark Office (PTO), for example, has seen a 500 per cent increase in the past five years in the number of patents issuing to Class 706, a classification exclusively designated for AI data processing systems.

Currently, inventors are individuals. But what if an AI-enabled machine invents something? What if an AI algorithm — without any human intervention — develops a new drug, a method of recognising diseases in medical images, or a new blade shape for a turbine? Section 100(f) of the Patent Act, 35 USCA Section 100(f) defines “inventor.” The legislative history of that section indicates that Congress intended statutory subject matter to “include anything under the sun that is made by man”, according to the US Supreme Court.[2] Accordingly, perhaps Congress, and not the courts, may have to make changes to existing patent law to address potentially patentable subject-matter developed autonomously by AI.

Underlying the patent laws is a contractual consideration. In exchange for a limited monopoly via a grant to exclude others from practising the claimed invention, an inventor must disclose to the public enough information about the invention to enable one of ordinary skills in the art to practice what is claimed.

Given the nature of some AI inventions, meeting this requirement can be challenging. For example, when seeking protection for rule-based AI systems, a research team may have developed rule sets that are effective for a specific application. Patent claims directed to a broader scope of application may not be enabled by the rules developed. Disclosing only those specific rules may not satisfy the disclosure obligations of Section 112 of the Patent Act, 35 USCA Section 112.

Similarly, the performance of AI embodied in artificial neural networks can depend on network topology, which can include the number and types of layers, the number of neurons per layer, neuron properties, training algorithms and training data sets. The scope of the claims will depend on what the limited set of topologies disclosed in the patent teaches one skilled in the art to practice.

In both the rule-based and network-based systems described above, where the systems have been developed heuristically, there may be questions regarding whether the patent discloses generalisations necessary to support the desired claim scope. There could be millions of permutations of the network architecture or rules adaptable for various applications.

Disclosing only a few and trying to define a broad claim scope may introduce risks. Providing a comprehensive disclosure laying out many embodiments may reduce some risk. But practically, how many can and should be disclosed? This is an area where guidance may come from the pharmaceutical arts, which may aid in an understanding of the bounds of patent disclosure and written description requirements.

Under Section 101 of the Patent Act, 35 US CA Section 101, the subject-matter of a patent claim must be directed to a “process, machine, manufacture or composition of matter”. However, the US Supreme Court held[3], that claims directed to nothing more than an abstract idea, such as a mathematical algorithm, or to natural phenomena or a law of nature are not eligible for patent protection. The technology underlying AI is generally based on computer programming or hardware implementing mathematical models, deep learning algorithms or a neural network. An improperly drafted patent application directed to AI may fall within this judicially recognised exception to patent-eligible subject-matter.

In Alice Corpn. Pty. Ltd. v. CLS Bank International[4], the Supreme Court provided the framework for determining “whether the claims at issue are directed to a patent-ineligible concept”. If the claims are, then the elements of all claims must be examined “to determine whether (they contain) an ‘inventive concept’ sufficient to ‘transform’ the claimed abstract idea into a patent-eligible application.”[5]

The US PTO expressly recognises that AI can be patentable through the express designation of Class 706, a section of the agency’s patent application classification system. In addition, two PTO “examining art units” for reviewing prior art are specifically devoted to reviewing applications directed toward AI algorithms.

Copyrights can be used as another form of protecting AI, because AI software can be copyrightable. In Synopsys Inc. v. ATopTech Inc.[6] Synopsys had patents directed to static timing analysis but instead relied exclusively on its copyrights of the software to secure a jury award of over $30 million based on ATopTech’s alleged infringement of Synopsys’ copyright.

Whether AI that is capable of generating copyrightable material can obtain a copyright is a different matter. A District Court recently found that a monkey had no rights to his selfie because the current copyright statute as interpreted affords rights to humans, not animals. This case demonstrates that future legislation would likely be required to allow animals, or AI for that matter, to obtain copyright protection.

AI and the IP issues it presents are continuing to evolve, creating a new frontier for businesses, governments, academicians and legislators. We need to consider changes in the law to employ the appropriate legal strategies to guide them as they deploy and protect AI-based innovations.

What can India do to Compete in the DT Space? Problems and Solutions

World Bank data estimates 69% of today’s jobs in India are threatened by AI-driven automation. China’s figure is 77%. Still, robots replacing jobs en masse is unrealistic in the medium term in India (or anywhere else) but the effects are already being felt. Last September, Indian textiles giant Raymond said it would replace 10,000 jobs with robots over three years. India lags well behind the developed world on labour productivity, which acts as a major drag on growth. We have to automate to be globally competent. Infrastructure supports productivity enabling to compete globally. The jobs of the future will focus on skills like critical thinking, collaboration and creativity. In this India’s education system also has a major role to be played, therefore it must prepare young people to participate and lead in the global DT industry.

Although the scenario has changed and India has realised that the Date is GOLD! India looks to “level playing field” with US tech giants. Indian lawmakers are looking for ways to curb the power of US tech giants with draft rules calling for companies to store local user data in India with the information accessible to the Government. The Wall Street Journal viewed a draft of a new e-commerce policy calling for a “level playing field” with rules for “encouraging domestic innovation and boosting the domestic digital economy to find its rightful place with dominant and potentially non-competitive global players”.[7]

Indian policymakers are looking for ways to tamp down American tech behemoths, a shift that could crimp growth potential in one of the biggest remaining open markets for their expansion. India wants to slap new rules on Amazon.com Inc., Apple Inc., Alphabet Inc.’s Google, Facebook Inc. and other firms, using a page from China’s playbook to take control of its citizens’ data and shelter homegrown startups. Lastly, in today’s DT space, India must develop indigenous capabilities in DT research involving all fields and build human capabilities in AI.

*Vaishali Singh is Research Associate, GNLU-Microsoft IPR Chair, Gujarat National Law University.

[1] See,?<https://www.researchgate.net/publication/310790993_Synergy_for_Digital_Transformation_Person’s_Multiple_Roles_and_Subject_Domains_Integration>.

[2] Diamond v. M. Chakrabarty, 1980 SCC OnLine US SC 128 : 65 L Ed 2d 144 : 447 US 303 (1980).

[3] Diamond v. R. Diehr, 1981 SCC OnLine US SC 41: 67 L Ed 2d 155: 450 US 175 (1981).

[4] 134 S. Ct. 2347.

[5] Ibid.

[6] 13–cv–02965–MMC(DMR).

[7] See, <https://seekingalpha.com/news/3382109-wsj-india-looks-level-playing-field-u-s-tech-giants>

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rolandfontana · 6 years ago

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New CFIUS Rules Shut Down Chinese Investment in U.S. Technology

Mergermarket, a leading U.S. mergers data reporter just published its global M&A report for 2018, revealing that investments from China in U.S. businesses fell by 95% as compared to 2016. A summary of the data in the Report shows the following:

1. Worldwide M&A activity was strong in 2018. “The transactions that did make it to the signing table reached USD 3.5tn worth of activity, ranking 2018 as the third-largest year on record by value. Average deal size saw its second-highest total value on record with USD 384.8m, just below the USD 400.3m peak reached in 2015.

2. Chinese investment in the U.S. virtually collapsed: “Chinese buys of US firms fell 94.6% to USD 3bn from a record USD 55.3bn in 2016.”

3. In response to being cut out of the United States, Chinese companies turned to Europe as a source of acquisition targets. “China’s bids in Europe increased 81.7% to USD 60.4bn from USD 33.2bn last year.”

Chinese companies did not lose interest in the United States. What happened is that the U.S. government’s security review system has made Chinese investment in any form of technology company virtually impossible. New legislation and regulations adopted in 2018 will make those investment barriers formal and permanent. These restrictions will survive any trade “deal” made on the current Section 301 tariff dispute with China. The investment restrictions have become part of the “new normal” in US-China economic relations.

How will this work? Foreign investment in the U.S. has long been controlled by the Committee on Foreign Investment in the United States (CFIUS) review process. This review procedure is managed by the Bureau of Industry and Security (BIS) of the Department of Commerce. In August of 2018, CFIUS’s jurisdiction was substantially expanded by the adoption of the Foreign Investment Risk Review Modernization Act (FIRRMA).

The new law expands CFIUS’s authority to review non-controlling investments by foreign companies (China) in U.S. companies that deal in critical and emerging technologies. As I previously reported in New Restrictions on High Tech Technology Transfers to China, BIS has begun rule-making to determine what specific technology will go on that list. The comment period for the rule making was extended to January 10, 2019 and as of right now, there are no reports on what exactly will go on the list.

BIS has though provided a listing of the general categories of technologies that will go on the list. I can simplify your review of this list (set forth below) by noting that it includes ANY form of technology in which a Chinese company would be interested.

1. Biotechnology, such as: (i) Nanobiology; (ii) Synthetic biology; (iii) Genomic and genetic engineering; or (iv) Neurotech

2. Artificial intelligence (AI) and machine learning technology, such as: (i) Neural networks and deep learning (e.g., brain modelling, time series prediction, classification); (ii) Evolution and genetic computation (e.g., genetic algorithms, genetic programming); (iii) Reinforcement learning; (iv)

3. Computer vision (e.g., object recognition, image understanding); (v) Expert systems (e.g., decision support systems, teaching systems); (vi) Speech and audio processing (e.g., speech recognition and production); (vii) Natural language processing (e.g., machine translation); (viii) Planning (e.g., scheduling, game playing); (ix) Audio and video manipulation technologies (e.g., voice cloning, deepfakes); (x) AI cloud technologies; or (xi) AI chipsets

4. Position, Navigation, and Timing (PNT) technology

5. Microprocessor technology, such as: (i) Systems-on-Chip (SoC); or (ii) Stacked Memory on Chip

6. Advanced computing technology, such as Memory-centric logic Data analytics technology, such as: (i) Visualization; (ii) Automated analysis algorithms; or (iii) Context-aware computing

7. Quantum information and sensing technology, such as: (i) Quantum computing; (ii) Quantum encryption; or (iii) Quantum sensing

8. Logistics technology, such as: (i) Mobile electric power; (ii) Modeling and simulation; (iii) Total asset visibility; or (iv) Distribution-based Logistics Systems (DBLS)

9. Additive manufacturing (e.g., 3D printing)

10. Robotics, such as: (i) Micro-drone and micro-robotic systems; (ii) Swarming technology; (iii) Self-assembling robots; (iv) Molecular robotics; (v) Robot compliers; or (vi) Smart Dust

11. Brain-computer interfaces, such as: (i) Neural-controlled interfaces; (ii) Mind-machine interfaces; (iii) Direct neural interfaces; or (iv) Brain-machine interfaces

12. Hypersonics, such as: (i) Flight control algorithms; (ii) Propulsion technologies; (iii) Thermal protection systems; or (iv) Specialized materials (for structures, sensors, etc.)

13. Advanced materials, such as: (i) Adaptive camouflage; (ii) Functional textiles (e.g., advanced fiber and fabric technology); or (iii) Biomaterials

14. Advanced surveillance technologies, such as Faceprint and voiceprint technologies.

BIS reports that it is considering expanding this list to cover a separate category of “critical infrastructure.” Though no proposed rule on this category has been issued, it is assumed this will include telecommunications, power generation (nuclear power), utilities and transport (high speed rail).

As you can see from the above, the list includes virtually everything a Chinese company would want in the technology sector. Chinese companies are still free to purchase U.S. real estate as long as the building is not located next to the Trump Tower in Manhattan and so long as they can get the money out of China to do so. See Getting Money out of China to Buy a House: Not Your Issue. Chinese companies are also presumably free to purchase nail salons, massage parlors, movie studios, restaurants, retail stores, and hotels. But anything in the technology sector will be hands off. Note that it is not even required that CFIUS ultimately reject the transaction. The public notice required by the new rules and the extended period for review is enough to kill most business deals. This seems to be one of the motivations for the new regulations: kill the deal before CFIUS is required to make a politically motivated decision.

Chinese companies saw the writing on the wall and abandoned investment in the U.S. in 2018. With the new CIFIUS rules on investing in emerging technology, this situation will become permanent. For that reason, U.S. technology start ups looking for investments from China should for the most part plan to look elsewhere.

As discussed above, Chinese companies are now looking to Europe as a replacement for the U.S. market in tech company investments. In my next post (after I meet with a contingent of our Spain lawyers who will be in town) I will discuss the restrictions on investment from China coming on line in Europe.

New CFIUS Rules Shut Down Chinese Investment in U.S. Technology syndicated from https://immigrationattorneyto.wordpress.com/

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repmywind02199 · 7 years ago

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Four short links: 30 November 2018

Advents are Coming, Open Source, Restricted Exports, and Misinformation Operations

QEMU Advent Calendar -- An amazing QEMU disk image every day!. It's that time of year again! See also Advent of Code.

De Facto Closed Source -- You want to download thousands of lines of useful, but random, code from the internet, for free, run it in a production web server, or worse, your user’s machine, trust it with your paying users’ data and reap that sweet dough. We all do. But then you can’t be bothered to check the license, understand the software you are running, and still want to blame the people who make your business a possibility when mistakes happen, while giving them nothing for it? This is both incompetence and entitlement.

U.S. Government Wonders What to Limit Exports Of -- The representative general categories of technology for which Commerce currently seeks to determine whether there are specific emerging technologies that are essential to the national security of the United States include: (1) Biotechnology, such as: (i) Nanobiology; (ii) Synthetic biology; (iv) Genomic and genetic engineering; or (v) Neurotech. (2) Artificial intelligence (AI) and machine learning technology, such as: (i) Neural networks and deep learning (e.g., brain modeling, time series prediction, classification); (ii) Evolution and genetic computation (e.g., genetic algorithms, genetic programming); (iii) Reinforcement learning; (iv) Computer vision (e.g., object recognition, image understanding); (v) Expert systems (e.g., decision support systems, teaching systems); (vi) Speech and audio processing (e.g., speech recognition and production); (vii) Natural language processing (e.g., machine translation); (viii) Planning (e.g., scheduling, game playing); (ix) Audio and video manipulation technologies (e.g., voice cloning, deepfakes); (x) AI cloud technologies; or (xi) AI chipsets. (3) Position, Navigation, and Timing (PNT) technology. (4) Microprocessor technology, such as: (i) Systems-on-Chip (SoC); or (ii) Stacked Memory on Chip. (5) Advanced computing technology, such as: (i) Memory-centric logic. (6) Data analytics technology, such as: (i) Visualization; (ii) Automated analysis algorithms; or (iii) Context-aware computing. (7) Quantum information and sensing technology, such as (i) Quantum computing; (ii) Quantum encryption; or (iii) Quantum sensing. (8) Logistics technology, such as: (i) Mobile electric power; (ii) Modeling and simulation; (iii) Total asset visibility; or (iv) Distribution-based Logistics Systems (DBLS). (9) Additive manufacturing (e.g., 3D printing); (10) Robotics such as: (i) Micro-drone and micro-robotic systems; (ii) Swarming technology; (iii) Self-assembling robots; (iv) Molecular robotics; (v) Robot compliers; or (vi) Smart Dust. (11) Brain-computer interfaces, such as (i) Neural-controlled interfaces; (ii) Mind-machine interfaces; (iii) Direct neural interfaces; or (iv) Brain-machine interfaces. (12) Hypersonics, such as: (i) Flight control algorithms; (ii) Propulsion technologies; (iii) Thermal protection systems; or (iv) Specialized materials (for structures, sensors, etc.). (13) Advanced Materials, such as: (i) Adaptive camouflage; (ii) Functional textiles (e.g., advanced fiber and fabric technology); or (iii) Biomaterials. (14) Advanced surveillance technologies, such as: Faceprint and voiceprint technologies. It's a great list of what's in the next Gartner Hype Cycle report.

The Digital Maginot Line (Renee DiResta) -- We know this is coming, and yet we’re doing very little to get ahead of it. No one is responsible for getting ahead of it. platforms aren’t incentivized to engage in the profoundly complex arms race against the worst actors when they can simply point to transparency reports showing that they caught a fair number of the mediocre actors. The regulators, meanwhile, have to avoid the temptation of quick wins on meaningless tactical bills (like the Bot Law) and wrestle instead with the longer-term problems of incentivizing the platforms to take on the worst offenders (oversight), and of developing a modern-day information operations doctrine.

Continue reading Four short links: 30 November 2018.

https://ift.tt/2QnuWfZ

#FEED 10 TECHNOLOGY

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doorrepcal33169 · 7 years ago

Text

Four short links: 30 November 2018

Advents are Coming, Open Source, Restricted Exports, and Misinformation Operations

QEMU Advent Calendar -- An amazing QEMU disk image every day!. It's that time of year again! See also Advent of Code.

Continue reading Four short links: 30 November 2018.

from FEED 10 TECHNOLOGY https://ift.tt/2QnuWfZ

#FEED 10 TECHNOLOGY

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nommedtail · 3 years ago

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project neural cloud is pretty good

#vii plays neural cloud #love the cat wearing a sweet jacket with a no touch patch

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nommedtail · 3 years ago

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finally flamebringer aki is home

#vii plays neural cloud #someone in my game support list def paid for his shards pack bc they have a shirtless aki lol #anyway simo is a good boi and i love that his pet ferret got digitized too

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nommedtail · 2 years ago

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octogen’s a tsundere...?!

#vii plays neural cloud #out of all the guys for the vday event he had the cutest one lol #why no gin or simo tho...

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nommedtail · 2 years ago

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python got them metal gear references

#vii plays neural cloud #project neural cloud

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nommedtail · 3 years ago

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sako nuzzle..

#vii plays neural cloud #he nuzzle and then they're both ready to attac..

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rolandfontana · 6 years ago

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New CFIUS Rules Shut Down Chinese Investment in U.S. Technology

2. Chinese investment in the U.S. virtually collapsed: “Chinese buys of US firms fell 94.6% to USD 3bn from a record USD 55.3bn in 2016.”

1. Biotechnology, such as: (i) Nanobiology; (ii) Synthetic biology; (iii) Genomic and genetic engineering; or (iv) Neurotech

4. Position, Navigation, and Timing (PNT) technology

5. Microprocessor technology, such as: (i) Systems-on-Chip (SoC); or (ii) Stacked Memory on Chip

6. Advanced computing technology, such as Memory-centric logic Data analytics technology, such as: (i) Visualization; (ii) Automated analysis algorithms; or (iii) Context-aware computing

7. Quantum information and sensing technology, such as: (i) Quantum computing; (ii) Quantum encryption; or (iii) Quantum sensing

8. Logistics technology, such as: (i) Mobile electric power; (ii) Modeling and simulation; (iii) Total asset visibility; or (iv) Distribution-based Logistics Systems (DBLS)

9. Additive manufacturing (e.g., 3D printing)

10. Robotics, such as: (i) Micro-drone and micro-robotic systems; (ii) Swarming technology; (iii) Self-assembling robots; (iv) Molecular robotics; (v) Robot compliers; or (vi) Smart Dust

11. Brain-computer interfaces, such as: (i) Neural-controlled interfaces; (ii) Mind-machine interfaces; (iii) Direct neural interfaces; or (iv) Brain-machine interfaces

12. Hypersonics, such as: (i) Flight control algorithms; (ii) Propulsion technologies; (iii) Thermal protection systems; or (iv) Specialized materials (for structures, sensors, etc.)

13. Advanced materials, such as: (i) Adaptive camouflage; (ii) Functional textiles (e.g., advanced fiber and fabric technology); or (iii) Biomaterials

14. Advanced surveillance technologies, such as Faceprint and voiceprint technologies.

New CFIUS Rules Shut Down Chinese Investment in U.S. Technology syndicated from https://immigrationattorneyto.wordpress.com/

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