A Clash of Cultures

November 8th, 2017

There’s an Internet controversy going on between Dale Dougherty, the CEO of Maker Media and Naomi Wu (@realsexycyborg), a Chinese Maker and Internet personality. Briefly, Dale Doughtery tweeted a single line questioning Naomi Wu’s authenticity, which is destroying Naomi’s reputation and livelihood in China.

In short, I am in support of Naomi Wu. Rather than let the Internet speculate on why, I am sharing my perspectives on the situation preemptively.

As with most Internet controversies, it’s messy and emotional. I will try my best to outline the biases and issues I have observed. Of course, everyone has their perspective; you don’t have to agree with mine. And I suspect many of my core audience will dislike and disagree with this post. However, the beginning of healing starts with sharing and listening. I will share, and I respectfully request that readers read the entire content of this post before attacking any individual point out of context.

The key forces I see at play are:

  1. Prototype Bias – how assumptions based on stereotypes influence the way we think and feel
  2. Idol Effect – the tendency to assign exaggerated capabilities and inflated expectations upon celebrities
  3. Power Asymmetry – those with more power have more influence, and should be held to a higher standard of accountability
  4. Guanxi Bias – the tendency to give foreign faces more credibility than local faces in China

All these forces came together in a perfect storm this past week.

1. Prototype Bias

If someone asked you to draw a picture of an engineer, who would you draw? As you draw the figure, the gender assigned is a reflection of your mental prototype of an engineer – your own prototype bias. Most will draw a male figure. Society is biased to assign high-level intellectual ability to males, and this bias starts at a young age. Situations that don’t fit into your prototypes can feel threatening; studies have shown that men defend their standing by undermining the success of women in STEM initiatives.

The bias is real and pervasive. For example, my co-founder in Chibitronics, Jie Qi, is female. The company is founded on technology that is a direct result of her MIT Media Lab PhD dissertation. She is the inventor of paper electronics. I am a supporting actor in her show. Despite laying this fact out repeatedly, she still receives comments and innuendo implying that I am the inventor or more influential than I really am in the development process.

Any engineer who observes a bias in a system and chooses not to pro-actively correct for it is either a bad engineer or they stand to benefit from the bias. So much of engineering is about compensating, trimming, and equalizing imperfections out of real systems: wrap a feedback loop around it, and force the error function to zero.

So when Jie and I stand on stage together, prototype bias causes people to assume I’m the one who invented the technology. Given that I’m aware of the bias, does it make sense to give us equal time on the stage? No – that would be like knowing there is uneven loss in a channel and then being surprised when certain frequency bands are suppressed by the time it hits the receivers. So, I make a conscious and deliberate effort to showcase her contributions and to ensure her voice is the first and last voice you hear.

Naomi Wu (pictured below) likely challenges your prototypical ideal of an engineer. I imagine many people feel a cognitive dissonance juxtaposing the label “engineer” or “Maker” with her appearance. The strength of that dissonant feeling is proportional to the amount of prototype bias you have.

I’ve been fortunate to experience breaking my own prototypical notions that associate certain dress norms with intelligence. I’m a regular at Burning Man, and my theme camp is dominated by scientists and engineers. I’ve discussed injection molding with men in pink tutus and learned about plasmonics from half-naked women. It’s not a big leap for me to accept Naomi as a Maker. I’m glad she’s challenging these biases. I do my best engineering when sitting half-naked at my desk. I find shirts and pants to be uncomfortable. I don’t have the strength to challenge these social norms, and secretly, I’m glad someone is.

Unfortunately, prototype bias is only the first challenge confronted in this situation.

2. Idol Effect

The Idol Effect is the tendency to assign exaggerated capabilities to public figures and celebrities. The adage “never meet your childhood hero” is a corollary of the Idol Effect – people have inflated expectations about what celebrities can do, so it’s often disappointing when you find out they are humans just like us.

One result of the Idol Effect is that people feel justified taking pot shots at public figures for their shortcomings. For example, I have had the great privilege of working with Edward Snowden. One of my favorite things about working with him is that he is humble and quick to correct misconceptions about his personal abilities. Because of his self-awareness of his limitations, it’s easier for me to trust his assertions, and he’s also a fast learner because he’s not afraid to ask questions. Notably, he’s never claimed to be a genius, so I’m always taken aback when intelligent people pull me aside and whisper in my ear, “You know, I hear Ed’s a n00b. He’s just using you.” Somehow, because of Ed’s worldwide level of fame that’s strongly associated with security technology, people assume he should be a genius level crypto-hacker and are quick to point out that he’s not. Really? Ed is risking his life because he believes in something. I admire his dedication to the cause, and I enjoy working with him because he’s got good ideas, a good heart, and he’s fun to be with.

Because I also have a public profile, the Idol Effect impacts me too. I’m bad at math, can’t tie knots, a mediocre programmer…the list goes on. If there’s firmware in a product I’ve touched, it’s likely to have been written by Sean ‘xobs’ Cross, not me. If there’s analytics or informatics involved, it’s likely my partner wrote the analysis scripts. She also edits all my blog posts (including this one) and has helped me craft my most viral tweets – because she’s a genius at informatics, she can run analyses on how to target key words and pick times of day to get maximum impact. The fact that I have a team of people helping me polish my work makes me look better than I really am, and people tend to assign capabilities to me that I don’t really have. Does this mean I am a front, fraud or a persona?

I imagine Naomi is a victim of Idol Effect too. Similar to Snowden, one of the reasons I’ve enjoyed interacting with Naomi is that she’s been quick to correct misconceptions about her abilities, she’s not afraid to ask for help, and she’s a quick learner. Though many may disapprove of her rhetoric on Twitter, please keep in mind English is her second language — her sole cultural context in which she learned English was via the Internet by reading social media and chat rooms.

Based on the rumors I’ve read, it seems fans and observers have inflated expectations for her abilities, and because of uncorrected prototype bias, she faces extra scrutiny to prove her abilities. Somehow the fact that she almost cuts her finger using a scraper to remove a 3D print is “evidence” that she’s not a Maker. If that’s true, I’m not a Maker either. I always have trouble releasing 3D prints from print stages. They’ve routinely popped off and flown across the room, and I’ve almost cut my fingers plenty of times with the scraper. But I still keep on trying and learning – that’s the point. And then there’s the suggestion that because a man holds the camera, he’s feeding her lines.

When a man harnesses the efforts of a team, they call him a CEO and give him a bonus. But when a woman harnesses the efforts of a team, she gets accused of being a persona and a front. This is uncorrected Prototype Bias meeting unrealistic expectations due to the Idol Effect.

The story might end there, but things recently got a whole lot worse…

3. Power Asymmetry

“With great power comes great responsibilities.”
-from Spider Man

Power is not distributed evenly in the world. That’s a fact of life. Not acknowledging the role power plays leads to systemic abuse, like those documented in the Caldbeck or Weinstein scandals.

Editors and journalists – those with direct control over what gets circulated in the media – have a lot of power. Their thoughts and opinions can reach and influence a massive population very quickly. Rumors are just rumors until media outlets breathe life into them, at which point they become an incurable cancer on someone’s career. Editors and journalists must be mindful of the power they wield and held accountable for when it is mis-used.

As CEO of Maker Media and head of an influential media outlet, especially among the DIY community, Dale Dougherty wields substantial power. So a tweet promulgating the idea that Naomi might be a persona or a fake does not land lightly. In the post-truth era, it’s especially incumbent upon traditional media to double-check rumors before citing them in any context.

What is personally disappointing is that Dale reached out to me on November 2nd with an email asking what I thought about an anonymous post that accused Naomi of being a fake. I vouched for Naomi as a real person and as a budding Maker; I wrote back to Dale that “I take the approach of interacting with her like any other enthusiastic, curious Maker and the resulting interactions have been positive. She’s a fast learner.”

Yet Dale decided to take an anonymous poster’s opinion over mine (despite a long working relationship with Make), and a few days later on November 5th he tweeted a link to the post suggesting Naomi could be a fake or a fraud, despite having evidence of the contrary.

So now Naomi, already facing prototype bias and idol-effect expectations, gets a big media personality with substantial power propagating rumors that she is a fake and a fraud.

But wait, it gets worse because Naomi is in China!

4. Guanxi Bias

In China, guanxi (关系) is everything. Public reputation is extremely hard to build, and quick to lose. Faking and cloning is a real problem, but it’s important to not lose sight of the fact that there are good, hard-working people in China as well. So how do the Chinese locals figure out who to trust? Guanxi is a major mechanism used inside China to sort the good from the bad – it’s a social network of credible people vouching for each other.

For better or for worse, the Chinese feel that Western faces and brands are more credible. The endorsement of a famous Western brand carries a lot of weight; for example Leonardo DiCaprio is the brand ambassador for BYD (a large Chinese car maker).

Maker Media has a massive reputation in China. From glitzy Maker Faires to the Communist party’s endorsement of Maker-ed and Maker spaces as a national objective, an association or the lack thereof with Maker Media can make or break a reputation. This is no exception for Naomi. Her uniqueness as a Maker combined with her talent at marketing has enabled her to do product reviews and endorsements as source of income.

However, for several years she’s been excluded from the Shenzhen Maker Faire lineup, even in events that she should have been a shoo-in for her: wearables, Maker fashion shows, 3D printing. Despite this lack of endorsement, she’s built her own social media follower base both inside and outside of China, and built a brand around herself.

Unfortunately, when the CEO of Maker Media, a white male leader of an established American brand, suggested Naomi was a potential fake, the Internet inside China exploded on her. Sponsors cancelled engagements with her. Followers turned into trolls. She can’t be seen publicly with men (because others will say the males are the real Maker, see “prototype bias”), and as a result faces a greater threat of physical violence.

A single innuendo, amplified by Power Asymmetry and Guanxi Bias, on top of Idol Effect meshed against Prototype Bias, has destroyed everything a Maker has worked so hard to build over the past few years.

If someone spread lies about you and destroyed your livelihood – what would you do? Everyone would react a little differently, but make no mistake: at this point she’s got nothing left to lose, and she’s very angry.

Reflection

Although Dale had issued a public apology about the rumors, the apology fixes her reputation as much as saying “sorry” repairs a vase smashed on the floor.

Image: Mindy Georges CC BY-NC

At this point you might ask — why would Dale want to slander Naomi?

I don’t know the background, but prior to Dale’s tweet, Naomi had aggressively dogged Dale and Make about Make’s lack of representation of women. Others have noted that Maker Media has a prototype bias toward white males. Watch this analysis by Leah Buechley, a former MIT Media Lab Professor:

Dale could have recognized and addressed this core issue of a lack of diversity. Instead, Dale elected to endorse unsubstantiated claims and destroy a young female Maker’s reputation and career.

Naomi has a long, uphill road ahead of her. On the other hand, I’m sure Dale will do fine – he’s charismatic, affable, and powerful.

When I sit and think, how would I feel if this happened to the women closest to me? I get goosebumps – the effect would be chilling; the combination of pervasive social biases would overwhelm logic and fact. So even though I may not agree with everything Naomi says or does, I have decided that in the bigger picture, hiding in complicit silence on the sidelines is not acceptable.

We need to acknowledge that prototype bias is real; if equality is the goal, we need to be proactive in correcting it. Just because someone is famous doesn’t mean they are perfect. People with power need to be held accountable in how they wield it. And finally, cross-cultural issues are complicated and delicate. All sides need to open their eyes, ears, and hearts and realize we’re all human. Tweets may seem like harmless pricks to the skin, but we all bleed when pricked. For humanity to survive, we need to stop pricking each other lest we all bleed to death.

/me dons asbestos suit

LiteX vs. Vivado: First Impressions

October 30th, 2017

Previously, I had written about developing a reference design for the NeTV2 FPGA using Xilinx’s Vivado toolchain. Last year at 33C3 Tim ‘mithro’ Ansell introduced me to LiteX and at his prompting I decided to give it a chance.

Vivado was empowering because instead of having to code up a complex SoC in Verilog, I could use their pseudo-GUI/TCL interface to create a block diagram that largely automated the task of building the AXI routing fabric. Furthermore, I could access Xilinx’s extensive IP library, which included a very flexible DDR memory controller and a well-vetted PCI-express controller. Because of this level of design automation and available IP, a task that would have taken perhaps months in Verilog alone could be completed in a few days with the help of Vivado.

The downsides of Vivado are that it’s not open source (free to download, but not free to modify), and that it’s not terribly efficient or speedy. Aside from the ideological objections to the closed-source nature of Vivado, there are some real, pragmatic impacts from the lack of source access. At a high level, Xilinx makes money selling FPGAs – silicon chips. However, to attract design wins they must provide design tools and an IP ecosystem. The development of this software is directly subsidized by the sale of chips.

This creates an interesting conflict of interest when it comes to the efficiency of the tools – that is, how good they are at optimizing designs to consume the least amount of silicon possible. Spending money to create area-efficient tools reduces revenue, as it would encourage customers to buy cheaper silicon.

As a result, the Vivado tool is pretty bad at optimizing designs for area. For example, the PCI express core – while extremely configurable and well-vetted – has no way to turn off the AXI slave bridge, even if you’re not using the interface. Even with the inputs unconnected or tied to ground, the logic optimizer won’t remove the unused gates. Unfortunately, this piece of dead logic consumes around 20% of my target FPGA’s capacity. I could only reclaim that space by hand-editing the machine-generated VHDL to comment out the slave bridge. It’s a simple enough thing to do, and it had no negative effects on the core’s functionality. But Xilinx has no incentive to add a GUI switch to disable the logic, because the extra gates encourage you to “upgrade” by one FPGA size if your design uses a PCI express core. Similarly, the DDR3 memory core devotes 70% of its substantial footprint to a “calibration” block. Calibration typically runs just once at boot, so the logic is idle during normal operation. With an FPGA, the smart thing to do would be to run the calibration, store the values, and then jam the pre-measured values into the application design, thus eliminating the overhead of the calibration block. However, I couldn’t implement this optimization since the DDR3 block is provided as an opaque netlist. Finally, the AXI fabric automation – while magical – scales poorly with the number of ports. In my most recent benchmark design done with Vivado, 50% of the chip is devoted to the routing fabric, 25% to the DDR3 block, and the remainder to my actual application logic.

Tim mentioned that he thought the same design when using LiteX would fit in a much smaller FPGA. He has been using LiteX to generate the FPGA “gateware” (bitstreams) to support his HDMI2USB video processing pipelines on various platforms, ranging from the Numato-Opsis to the Atlys, and he even started a port for the NeTV2. Intrigued, I decided to port one of my Vivado designs to LiteX so that I could do an apples-to-apples comparison of the two design flows.

LiteX is a soft-fork of Migen/MiSoC – a python-based framework for managing hardware IP and auto-generating HDL. The IP blocks within LiteX are completely open source, and so can be targeted across multiple FPGA architectures. However, for low-level synthesis, place & route, and bitstream generation, it still relies upon proprietary chip-specific vendor tools, such as Vivado when targeting Artix FPGAs. It’s a little bit like an open source C compiler that spits out assembly, so it still requires vendor-specific assemblers, linkers, and binutils. While it may seem backward to open the compiler before the assembler, remember that for software, an assembler’s scope of work is simple — primarily within well-defined 32-bit or so opcodes. However, for FPGAs, the “assembler” (place and route tool) has the job of figuring out where to place single-bit primitives within an “opcode” that’s effectively several million bits long, with potential cross-dependencies between every bit. The abstraction layers, while parallel, aren’t directly comparable.

Let me preface my experience with the statement that I have a love-hate relationship with Python. I’ve used Python a few times for “recreational” projects and small tools, and for driving bits of automation frameworks. But I’ve found Python to be terribly frustrating. If you can use their frameworks from the ground-up, it’s intuitive, fun, even empowering. But if your application isn’t naturally “Pythonic”, woe to you. And I have a lot of needs for bit-banging, manipulating binary files, or grappling with low-level hardware registers, activities that are decidedly not Pythonic. I also spend a lot of time fighting with the “cuteness” of the Python type system and syntax: I’m more of a Rust person. I like strictly typed languages. I am not fond of novelties like using “-1” as the last-element array index and overloading the heck out of binary operators using magic methods.



Comics courtesy of xkcd, CC BY-NC-2.5

Surprisingly, I was able to get LiteX up and running within a day. This is thanks in large part to Tim’s effort to create a really comprehensive bootstrapping script that checks out the git repo, all of the submodules (thank you!), and manages your build environment. It just worked; the only bump I encountered was a bit of inconsistent documentation on installing the Xilinx toolchain (for Artix builds you need to grab Vivado; and Spartan you grab ISE). The whole thing ate about 19GiB of hard drive space, of which 18GiB is the Vivado toolchain.

I was rewarded with a surprisingly powerful and mature framework for defining SoCs. Thanks to the extensive work of the MiSoC and LiteX crowd, there’s already IP cores for DRAM, PCI express, ethernet, video, a softcore CPU (your choice of or1k or lm32) and more. To be fair, I haven’t been able to load these on real hardware and validate their spec-compliance or functionality, but they seem to compile down to the right primitives so they’ve got the right shape and size. Instead of AXI, they’re using Wishbone for their fabric. It’s not clear to me yet how bandwidth-efficient the MiSoC fabric generator is, but the fact that it’s already in use to route 4x HDMI connections to DRAM on the Numato-Opsis would indicate that it’s got enough horsepower for my application (which only requires 3x HDMI connections).

As a high-level framework, it’s pretty magical. Large IP instances and corresponding bus ports are allocated on-demand, based on a very high level description in Python. I feel a bit like a toddler who has been handed a loaded gun with the safety off. I’m praying the underlying layers are making sane inferences. But, at least in the case of LiteX, if I don’t agree with the decisions, it’s open source enough that I could try to fix things, assuming I have the time and gumption to do so.

For my tool flow comparison, I implemented a simple 2x HDMI-in to DDR3 to 1x HDMI-out design in both Vivado and in LiteX. Creating the designs is about the same effort on both flows – once you have the basic IP blocks, instantiating bus fabric and allocation of addressing is largely automated in each case. Vivado is superior for pin/package layout thanks to its graphical planning tool (I find an illustration of the package layout to be much more intuitive than a textual list of ball-grid coordinates), and LiteX is a bit faster for design creation despite the usual frustrations I have with Python (up to the reader’s bias to decide whether it’s just that I have a different way of seeing things or if my intellect is insufficient to fully appreciate the goodness that is Python).


Pad layout planning in Vivado is aided by a GUI


Example of LiteX syntax for pin constraints

But from there, the experience between the two diverges rapidly. The main thing that’s got me excited about LiteX is the speed and efficiency of its high-level synthesis. LiteX produces a design that uses about 20% of an XC7A50 FPGA with a runtime of about 10 minutes, whereas Vivado produces a design that consumes 85% of the same FPGA with a runtime of about 30-45 minutes.

Significantly, LiteX tends to “fail fast”, so syntax errors or small problems with configurations become obvious within a few seconds, if not a couple minutes. However, Vivado tends to “fail late” – a small configuration problem may not pop up until about 20 minutes into the run, due to the clumsy way it manages out-of-context block synthesis and build dependencies. This means that despite my frustrations with the Python syntax, the penalty paid for small errors is much less in terms of time – so overall, I’m more productive.

But the really compelling point is the efficiency. The fact that LiteX generates more efficient HDL means I can potentially shave a significant amount of cost out of a design by going to a smaller FPGA. Remember, both LiteX and Vivado use the same back-end for low-level sythesis and place and route. The difference is entirely in the high-level design automation – and this is a level that I can see being a good match for a Python-based framework. You’re not really designing hardware with Python (eventually it all turns into Verilog) so much as managing and configuring libraries of IP, something that Python is quite well suited for. To wit, I dug around in the MiSoC libraries a bit and there seem to be some serious logic designs using this Python syntax. I’m not sure I want to wrap my head around this coding style, but the good news is I can still write my leaf cells in Verilog and call them from the high-level Python integration framework.

So, I’m cautiously proceeding to use LiteX as the main design flow going forward for NeTV2. We’ll see how the bitstream proves out in terms of timing and functionality once my next generation hardware is available, but I’m optimistic. I have a few concerns about how debugging will work – I’ve found the Xilinx ILA cores to be extremely powerful tools and the ability to automatically reverse engineer any complex design into a schematic (a feature built into Vivado) helps immensely with finding timing and logic bugs. But with a built-in soft CPU core, the “LiteScope” logic analyzer (with sigrok support coming soon), and fast build times, I have a feeling there is ample opportunity to develop new, perhaps even more powerful methods within LiteX to track down tricky bugs.

My final thought is that LiteX, in its current state, is probably best suited for people trained to write software who want to design hardware, rather than for people classically trained in circuit design who want a tool upgrade. The design idioms and intuitions built into LiteX pulls strongly from the practices of software designers, which means a lot of “obvious” things are left undocumented that will throw outsiders (e.g. hardware designers like me) for a loop. There’s no question about the power and utility of the design flow – so, as the toolchain matures and documentation improves I’m optimistic that this could become a popular design flow for hardware projects of all magnitudes.


Interested? Tim has suggested the following links for further reading:

Name that Ware October 2017

October 26th, 2017

The Ware for October 2017 is shown below.

Sometimes a ware just presents itself to you among your travels; thankfully cell phone cameras have come a long way.

Winner, Name that Ware September 2017

October 26th, 2017

The Ware for September 2017 is a WP 5007 Electrometer. I’ll give this one to Ingo, for the first mention of an electrometer. Congrats, email me for your prize! And @zebonaut, agreed, polystyrene caps FTW :)

Why I’m Using Bitmarks on my Products

October 13th, 2017

One dirty secret of hardware is that a profitable business isn’t just about design innovation, or even product cost reduction: it’s also about how efficiently one can move stuff from point A to B. This explains the insane density of hardware suppliers around Shenzhen; it explains the success of Ikea’s flat-packed furniture model; and it explains the rise of Amazon’s highly centralized, highly automated warehouses.

Unfortunately, reverse logistics – the system for handling returns & exchanges of hardware products – is not something on the forefront of a hardware startup’s agenda. In order to deal with defective products, one has to ship a product first – an all-consuming goal. However, leaving reverse logistics as a “we’ll fix it after we ship” detail could saddle the venture with significant unanticipated customer support costs, potentially putting the entire business model at risk.

This is because logistics are much more efficient in the “forward” direction: the cost of a centralized warehouse to deliver packages to an end consumer’s home address is orders of magnitude less than it is for a residential consumer to mail that same parcel back to the warehouse. This explains the miracle of Amazon Prime, when overnighting a pair of hand-knit mittens to your mother somehow costs you $20. Now repeat the hand-knit mittens thought experiment and replace it with a big-screen TV that has to find its way back to a factory in Shenzhen. Because the return shipment can no longer take advantage of bulk shipping discounts, the postage to China is likely more than the cost of the product itself!

Because of the asymmetry in forward versus reverse logistics cost, it’s generally not cost effective to send defective material directly back to the original factory for refurbishing, recycling, or repair. In many cases the cost of the return label plus the customer support agent’s time will exceed the cost of the product. This friction in repatriating defective product creates opportunities for unscrupulous middlemen to commit warranty fraud.

The basic scam works like this: a customer calls in with a defective product and gets sent a replacement. The returned product is sent to a local processing center, where it may be declared unsalvageable and slated for disposal. However, instead of a proper disposal, the defective goods “escape” the processing center and are resold as new to a different customer. The duped customer then calls in to exchange the same defective product and gets sent a replacement. Rinse lather repeat, and someone gets rich quick selling scrap at full market value.

Similarly, high-quality counterfeits can sap profits from companies. Clones of products are typically produced using cut-rate or recycled parts but sold at full price. What happens when customers then find quality issues with the clone? That’s right – they call the authentic brand vendor and ask for an exchange. In this case, the brand makes zero money on the customer but incurs the full cost of supporting a defective product. This kind of warranty fraud is pandemic in smart phones and can cost producers many millions of dollars per year in losses.


High-quality clones, like the card on the left, can cost businesses millions of dollars in warranty fraud claims.

Serial numbers help mitigate these problems, but it’s easy to guess a simple serial number. More sophisticated schemes tie serial numbers to silicon IDs, but that necessitates a system which can reliably download the serialization data from the factory. This might seem a trivial task but for a lot of reasons – from failures in storage media to human error to poor Internet connectivity in factories – it’s much harder than it seems to make this happen. And for a startup, losing an entire lot of serialization data due to a botched upload could prove fatal.

As a result, most hardware startups ship products with little to no plan for product serialization, much less a plan for reverse logistics. When the first email arrives from an unhappy customer, panic ensues, and the situation is quickly resolved, but by the time the product arrives back at the factory, the freight charges alone might be in the hundreds of dollars. Repeat this exercise a few dozen times, and any hope for a profitable run is rapidly wiped out.

I’ve wrestled with this problem on and off through several startups of my own and finally landed on a solution that looks promising: it’s reasonably robust, fraud-resistant, and dead simple to implement. The key is the bitmark – a small piece of digital data that links physical products to the blockchain.

Most people are familiar with blockchains through Bitcoin. Bitcoin uses the blockchain as a public ledger to prevent double-spending of the same virtual coin. This same public ledger can be applied to physical hardware products through a bitmark. Products that have been bitmarked can have their provenance tracked back to the factory using the public ledger, thus hampering cloning and warranty fraud – the physical equivalent of double-spending a Bitcoin.

One of my most recent hardware startups, Chibitronics has teamed up with Bitmark to develop an end-to-end solution for Chibitronics’ newest microcontroller product, the Chibi Chip.

As an open hardware business, we welcome people to make their own versions of our product, but we can’t afford to give free Chibi Chips to customers that bought cut-rate clones and then report them as defective for a free upgrade to an authentic unit. We’re also an extremely lean startup, so we can’t afford the personnel to build a full serialization and reverse logistics system from scratch. This is where Bitmark comes in.

Bitmark has developed a turn-key solution for serialization and reverse logistics triage. They issue us bitmarks as lists of unique, six-word phrases. The six-word phrases are less frustrating for users to type in than strings of random characters. We then print the phrases onto labels that are stuck onto the back of each Chibi Chip.


Bitmark claim code on the back of a Chibi Chip

We release just enough of these pre-printed labels to the factory to run our authorized production quantities. This allows us to trace a bitmark back to a given production lot. It also prevents “ghost shifting” – that is, authorized factories producing extra bootleg units on a midnight shift that are sold into the market at deep discounts. Bitmark created a website for us where customers can then claim their bitmarks, thus registering their product and making it eligible for warranty service. In the event of an exchange or return, the product’s bitmark is updated to record this event. Then if a product fails to be returned to the factory, it can’t be re-claimed as defective because the blockchain ledger would evidence that bitmark as being mapped to a previously returned product. This allows us to defer the repatriation of the product to the factory. It also enables us to use unverified third parties to handle returned goods, giving us a large range of options to reduce reverse logistics costs.

Bitmark also plans to roll out a site where users can verify the provenance of their bitmarks, so buyers can check if a product’s bitmark is authentic and if it has been previously returned for problems before they buy it. This increases the buyer’s confidence, thus potentially boosting the resale value of used Chibi Chips.

For the cost and convenience of a humble printed label, Bitmark enhances control over our factories, enables production lot traceability, deters cloning, prevents warranty fraud, enhances confidence in the secondary market, and gives us ample options to streamline our reverse logistics.

Of course, the solution isn’t perfect. A printed label can be peeled off one product and stuck on another, so people could potentially just peel labels off good products and resell the labels to users with broken clones looking to upgrade by committing warranty fraud. This scenario could be mitigated by using tamper-resistant labels. And for every label that’s copied by a cloner, there’s one victim who will have trouble getting support on an authentic unit. Also, if users are generally lax about claiming their bitmark codes, it creates an opportunity for labels to be sparsely duplicated in an effort to ghost-shift/clone without being detected; but this can be mitigated with a website update that encouraging customers to immediately register their bitmarks before using the web-based services tied to the product. We also have to exercise care in handling lists of unclaimed phrases because, until a customer registers their bitmark claim phrase in the blockchain, the phrases have value to would-be fraudsters.

But overall, for the cost and convenience, the solution outperforms all the other alternatives I’ve explored to date. And perhaps most importantly for hardware startups like mine that are short on time and long on tasks, printing bitmarks is simple enough for us to implement that it’s hard to justify doing anything else.

Disclosure: I am a technical advisor and shareholder of Bitmark.