• Most interesting technology developments and IP issues of 2017

  • TechInsights tears down hundreds of advanced technology devices every year. We monitor emerging technology trends, analyze devices and report our findings, and we assist IP teams, lawyers, product managers, engineers, and more by providing them with factual, technical data and analysis about advanced technology products.

    And all of that requires the coordinated efforts of a large, very talented, dedicated team of patent and technology experts.

    We asked our team what they thought were the most interesting developments in their respective fields in 2017. Here are some of their answers:


    Art Monk, Vice President, Patent Transactions, IP Services, San Jose:

    • Oil States v. Green’s Energy: Clearly the outcome of this SCOTUS proceeding will be known in 2018, however the fact that SCOTUS agreed to hear the case (request for Cert.) was a major development in the IP space.
    • TC Heartland v. Kraft Foods: This case led to requiring patentees to sue corporate infringers only in the districts where they are incorporated, or committed acts of infringement, and have a valid business presence. This led to many cases being transferred out of the Eastern District of Texas (famous for its plaintiff-friendly juries and “rocket docket”), now Delaware is overloaded.
    • Introduction of the STRONGER Patents Act (S. 1390): Provides many adjustments to AIA that have been championed by the Pro-Patent communit

    Most interesting IP issues in 2017


    Carlos Lopez, Solutions Architect, IP Services, Ottawa:

    2017 saw Artificial Intelligence (AI) technology being applied in increasingly useful ways in different areas of technology.  Some examples:

    • Speech recognition / speech generation in automated dial-in systems that interact with clients. This varies from call center-type applications to products like Siri and Google Assistant. Companies operating in this space include Cambridge Semantics and Digital Reasoning.
    • Machine Learning - This is the application of AI to analytics such as sales projections and the like. Examples of companies operating in this space include Google, Microsoft and Fractal Analytics.
    • Biometric security - This is used to learn biometrics and adjust them over time. FaceFirst is an example of a company operating in this space.
    • Automotive - Assisted driving , image and optical recognition. There was a virtual explosion of companies operating in this space in 2017.

    AI is being applied in increasingly useful ways


    Chris Pawlowicz, Director, Operations R&D, Ottawa:

    I have noticed a big ramp up in attention towards hardware security, specifically around unwanted circuitry and additional functionality embedded in integrated circuits manufactured in Asia. The need for the ability to reverse engineer ICs made off-shore so that you can detect and identify Trojans within the hardware is now centre stage.

    This year the US Intelligence community (Office of the Director of National Intelligence) kicked off a research initiative worth 10’s of millions of dollars to develop technology for quickly reverse-engineering ICs.

    Conferences such as the International Symposium for Testing and Failure Analysis (ISTFA) have always been interested in reverse engineering but as a background activity and geared towards failure analysis- 2017 saw it become a legitimate technical stream in its own right (Hardware Attacks, Security and Reverse Engineering).

    2017 saw a ramp up in hardware security

    Even IC companies are concerned- many use 3rd party ‘IP cores’ (licensed chip functionality that whey will include in their IC) but they are not really sure if the design they are including in their chip is secure. I’ve talked with people working in the security divisions at large IC companies and they are struggling with this growing concern.


    Dick James, TechInsights Fellow Emeritus, Ottawa:

    I think that it’s worth commenting that the motherboard in the iPhone X is VERY different, as indicated in a cross-section of the assembly.

    (The motherboard in the iPhone X moved away from the traditional L-shape to a stacked architecture)

    Cross section of Apple iPhone X motherboard  


    Ian MacLean, Vice President, Intellectual Property Services, Ottawa:

    There is still significant interest around the IP play in IoT and Automotive but, pragmatically speaking, the market realization hasn’t happened at the originally-expected pace, and there is still a significant “wait and see” aspect as to how it’s going to play out.

    IP strategy in IoT and Automotive taking shape


    Albert Cowsky, Manager, Costing Analysis, Chicago:

    Different costing approaches to flagship phones were a key area of interest in 2017.

    The table below provides our costing analysis comparison on the iPhone X, iPhone 8, Samsung Galaxy S8, and Huawei Mate 10.

    The Apple iPhone 8 and Huawei Mate 10 have very similar costing models, with margins of 59.3% and 59.2%, respectively. The costs of goods sold (COGS) of the iPhone X and the Galaxy S8 are within $70 of each other, but at $999 and $725, respectively, they are significantly farther apart on sticker price. The result is a 5.5% difference in margin between the two.

    iPhone X, iPhone 8, Samsung Galaxy S8, and Huawei Mate 10  

    Device Apple iPhone X A1901
    (Preliminary Deep Dive Data)
    iPhone 8 A1905
    (Deep Dive)
    Samsung Galaxy S8 SM-G950F
    (Deep Dive)
    Huawei Mate 10
    (QTT)
    Sticker Price $999.00 $699.00 $725.00 $710.00
    COGS $395.00 $284.52 $326.50 $290.00
    Margin 60.5% 59.3% 55.0% 59.2%


    Ray Fontaine, Senior Technical Analyst specializing in semiconductor fabrication process analysis and image sensors, Ottawa:

    Cameras

    2017 may be remembered as the year that camera and sensing systems became the undisputed kings of differentiation across smartphone platforms…

    …As we end 2017 we are happy to announce we have found 0.9 µm generation pixels in mass production!...

    Samsung 0.9 µm Generation ISOCELL with Tetracell Color Filters  

    Chip Stacking for Image Sensors

    Chip stacking (image sensor + image signal processor) for image sensors remains an enabling technology for improved camera performance, and this year we documented Sony’s first-generation TSV-based three die stack (now adding a DRAM) in mass production…

    Improved Near Infrared Sensitivity

    Moving outside of traditional array imaging, another trend we’ve tracked in 2017 is the continued emergence of cameras with improved near infrared (NIR) sensitivity…

    Looking Ahead

    There is, of course, much more happening in the imaging sector than can be conveyed in this summary.  We have seen high quality imaging-related papers from IISW, IEDM, ISSCC, and other conferences, so it’s a good indication of continued development of disruptive imaging/sensing platforms. We’ll be tracking these announced and stealth mode technologies expected in 2018 product launches.

    You can read Ray’s full post about Noteworthy Developments in Image Sensor Technology in 2017 here.


    Christie Thompson, Director of Marketing Operations, Ottawa

    Of course, we would be remiss if we didn’t mention the technological innovations that we, as a company, focused on in 2017.

    Some of our larger analysis projects, and projects that garnered the most interest, focused on the following technologies:

    Samsung 18 nm DRAM
    Intel/Micron 64L 3D NAND
    TSMC 10 nm Process
    Intel 3D XPoint
    Sony IMX400 3-Layer Stacked (Exmor RS) CMOS Image Sensor
    Samsung 10 nm LPE Process
    Qualcomm RF360
    Samsung’s Read Retry for 3D NAND

    Samsung 18 nm DRAM  


    Clearly, TechInsights found 2017 to be a very interesting year. Let’s see what 2018 brings!

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