Conferences in 2019

As Christmas and New Year holidays are coming up, I wanted to reflect on two conferences in two different countries -- Estonia and Ukraine, that I had a pleasure to participate and / or organize this year.

AINL

AINL Conference (https://ainlconf.ru/2019/program), held in Tartu in November, focused a lot on applying deep learning to NLProc, with two tutorials by Dmitry Ustalov (Yandex) on Crowdsourcing on Language Resources and Evaluation and by Andrey Kutuzov (University of Oslo) on Diachronic Word Embeddings for Semantic Shifts Modelling. Andrey Kutuzov's tutorial was practical and involved some Python coding, resulting in a pull request: https://github.com/wadimiusz/diachrony_for_russian/pull/5 that I submitted for the task of comparing semantic shifts in meaning between Soviet and Post Soviet eras. This code uses Jaccard similarity as a local method for detecting shifts in meaning. There are also global methods, like Procrustes alignment, the only downside of which is it is slower, than Jaccard. You can read more detail on the task in Andrey's AINL slides.

Credit: Dmitry Kan

In terms of submitted papers -- the review process was double-blind and involved at least 3 reviewers per paper. The result was 30% acceptance rate and 12 out of 40 papers that did make it, focused on data acquisition and annotation, human-computer interaction, statistical NLProc (including paper by Ansis Bērziņš on usage of speech recognition for determining language similarity -- video) and neural language models (one of the works for morpheme segmentation using Bi-LSTM model cited the work of Mathias Creutz with whom we worked at AlphaSense 2010-2016).

Last day of the conference focused on the industrial applications of AI in NLProc. By invitation of Lidia Pivovarova (University of Helsinki) I presented on the search engine and NLProc work we've done at AlphaSense, including smart synonyms, sentiment analysis, named entity recognition and salience resolution, theme modelling and high-precision search.

One of the challenges for the industrial presentation was that it had to last for 1,5 hours. If you consider your audience ability to focus only for 40 minutes, you have got to do something else than 65 slides. I decided to make about 30 slides and then handle the rest of my talk with Q&A. The outcome has been very surprising to myself, because the audience did want to learn details of AlphaSense product, making the Q&A last for 50 minutes. Quite a few questions I managed to answer with the product itself -- this sparks genuine interest in understanding the UI of an AI product powering the financial industry. I hope this was beneficial for the audience to dive into the workflows of financial knowledge workers and how NLProc can help solve their daily routine tasks better.

Customer Development Marathon

Customer development is the topic that interests me from the point of the product development. Just recently I've learnt about jobs-to-be-done approach to mining for real jobs that your customers hire your product for. One example with which Clayton Christensen of Harvard Business School motivates this approach is the job that male consumers of milkshakes had on the their way to work every day: stay engaged in life during monotonous driving and stay full until 10 a.m.

The conference (or marathon as we called it) on customer development attracted 70 participants at iHUB co-working center in Kyiv, Ukraine. Speakers from various established companies -- YouScan, MacPaw, PromoRepublic, Competera, AlphaSense, Kyivstar, Terrasoft, PMLab, Portmone.com, Weblium, VARUS, SendPulse, EVO.company -- presented 5 min talks about specific cases on engaging with their customers to grow conversion, retention and happiness with their products. Following the presentations, the discussion panels dug deeper into how to implement a customer-centric business. 

Credit: Maria Kudinova

We've organized the marathon in 3 panels: 

1. Idea. Analysis. Validation 
2. Creation. Delivery. Launch and
3. Sales. Feedback. Innovation. 

Each of these panels focused on a particular stage of product development from idea to post-sale feedback and innovation loop. The audience learnt about how to conduct an efficient user interview, what tools help reach out to new or existing clients, how not to push your product into consulting or outsource, how to establish an internal company-wide communication to stay on the same page when shaping the product, marketing and sales around customer needs.

Both events were full of networking, meeting new and familiar faces in the industry and academia and learning a lot. For anything you aspire to build next year, focusing on real value and ease of use of your NLP / AI / search products, and thinking what job your users hire your products for will help you serve them better.

Eight thoughts on revolutionary changes

The Martian is my top favourite movie (and a book) that in action shows the excitement around engineering professions. Mark Watney, being left alone on Mars, fights for his life with all the knowledge and skills he has, from botany to chemistry and physics. Of all engineering professions, software engineering is probably the most booming right now in light of Artificial Intelligence breakthroughs. But does this profession have ethical aspects that we as engineers and humans need to be continuously thinking about?

I began to follow the work of Yuval Noah Harari and his call to the humanity on a potential big issue we are facing. It does not yet dawn at many of us to start thinking about potential threats to how we operate today. Many of us focus on day-to-day activities and may not have enough time to look beyond.

Right now I see two figures on the global scene that publicly speak with some urgency about AI, its potentially disruptive impact and change for the civilisation. Yuval Noah claims we are at a cross-road of getting new types of human beings, that will have supporting AI and biological improvements made to them. Elon Musk claims that AI is way smarter than human already (take Go) and we need to start thinking how to control it. And AI keeps improving for higher and higher degrees of freedom (from checkers, through chess, to Go it is a few orders of magnitude change in degrees of freedom each game allows). And so eventually AI will beat human beings in what is possible. One of the contemporary examples touching me personally is robots ironing clothes or wiping off coffee spills with high level of movement precision and similarity to that of humans:

https://twitter.com/pabbeel/status/1115642512603897856

Very excited to announce a project 3 years in the making: BLUE, a low-cost, safe, capable robot designed from the ground up with AI in mind.

Want BLUE? You can now sign up for priority access here: https://t.co/bdK7ouRABK

Learn more here: https://t.co/vB0i39aHTE

w/@Cthephen pic.twitter.com/Ucxqyylzue

— Pieter Abbeel (@pabbeel) April 9, 2019

But I’m sure Musk and Harari mean more than that.

A simple example Harari gives is: the IoT devices will record your pulse / level of endorphines as you see your political leader and so the government will know, how happy and faithful you are towards your leadership. Or what ads to show you depending on your sexual orientation based on what you have written / read / watched (even well before you understand your orientation yourself).

When more and more AI powered robots will take away the routine tasks, we as humanity will have two development paths: wear complacency and become lazier or seek creativeness. The first path is always reachable, especially in the time when we would work 3 days a week, 4 hours a day (by Jack Ma’s prediction). Will AI thus become even more dominant and take the lead over humanity? As by Musk eventually AI will write its own software and will be way more efficient in it, than modern AI engineers. And at some point humans having slower interfaces to produce / consume data and knowledge will be left behind AI and it can turn into a catch up game.

Given these potential issues that automation with AI is posing, those of us who focus on automation and AI touch on the ethical boundaries of our work. If you will, we are participating in the launch and acceleration of an AI revolution, that might not be visible for all people on the Planet yet. But we need to be aware of changing the society fabrics through rewriting job markets, work skills in demand and allowing new types of human / robot elites control people around them with AI.

I would like to share a different perspective on revolutions, Planet-agnostic:

1. Making an industry level revolution is hard. There are many reasons, one of which is simply human laziness. Who in their sane mind would want to change anything in the production process, when it is comfortable as is?
2. The revolution force should be so strong, that it is able to cover individual and collective laziness / resistance and still be obvious to anyone involved, that it is a change for good.
3. As we progress into the future, multiple of these (small and big) revolutions will make life easier and hence more lazy participants will emerge.
4. When laziness saturates, what direction the next revolution will take and will it really optimise for making things globally sustainable (like climate or flying to Mars) or locally to cater to individual’s needs to make us even more complacent?
5. This leaves true revolution breakthroughs to unsettled minds, challenging everything they see. Which makes such people highly uncomfortable for lazy ones to be around.
6. And naturally, the unsettled minds don’t have much time to enjoy the results of their doing (assuming the time span of a revolution is less than their lifespan).
7. Yet lazy will eventually benefit from these revolutions and become lazier.
8. The question then is: how to optimise for a global goal, while making as many on the Planet involved to keep knowledge and revolution results more evenly distributed?

I thank Derek Kannenberg and Tatiana Batanina for reading drafts of this essay and providing constructive feedback and thoughts.

Originally published at https://www.linkedin.com.

Company culture

Long gone are the days, when company culture did not matter or was a second-class citizen. Today, when choosing a company to work for, above all you choose the culture (may be even not realizing it and thinking that you are after technology or product). When you look at the job openings or office photos with employee smiles and general cheering atmosphere you will likely not see the culture of the company. You may get a glimpse of it during the interview process, but it is not enough.

Credit: https://www.inc.com/marla-tabaka/7-elements-of-a-great-company-culture.html

Why is culture important?

What is culture? Citing Wikipedia:

Culture (/ˈkʌltʃər/) is the social behavior and norms found in human societies.

To me company culture boils down to every day activities, like running projects, exchanging information and planning. I do not think that culture can be imposed. Observing it and declaring core values however makes sense.

You can make a simple test to see the edges of your culture: if you have two employees sharing the same language talking in the kitchen and third one -- of different nation -- enters, will the first two switch to a common to all three language? You can argue they don't have to. And this is where the culture begins: is it inclusive? Is it about socializing together or in smaller groups? This in turn will most likely affect on collaborativeness level amongst these groups during real projects.

Beyond language, there are many aspects of culture that directly impact the results of a company. Take decision making for one. When conflicting parties meet to discuss a pressing matter -- how will they exchange ideas? In what fashion will they criticize each other's ideas?

How to criticize successfully: pic.twitter.com/m91LVIReP5

— Nat Friedman (@natfriedman) April 13, 2019

Why all this is of such importance? Well, it depends. Some will say -- "we don't care about the internal kitchen of how a result was achieved". But you can also ask yourself: what kind of place you would like to work at? Is it something where everyone contributes their share and want to be heard? Or is it the place where everyone (100% inclusively) knows that sharing ideas will be supported no matter how smart or stupid an idea is? "What does it matter, if the result is what it is" -- you may argue. If you are building a great place to work, you would like to make it great for everyone, not just a few. And the hardest part is to re-evaluate your culture as if you just joined the company (really hard, I know).

Ingredients of a solid culture

Building a good culture is a process that should evolve. There will be new people joining and new teams forming around these people. Through the lens of working in several small and mid-size companies (with hundreds of employees) I found the following ingredients of a company culture to really make a difference specifically for IT product companies.

1. Readiness to support. Do your engineers willingly walk an extra mile to support each other? Beyond sprint meetings, calls with product managers and status updates. Do they walk around the office / scan work chat and ask if they could help in passing? If there is a culture of support it prompts a lot of things to happen, like idea formation, knowledge sharing and general positive vibe in the office / chat. This combined makes work not only fun, but also more efficient. Again what to watch for here is "abuse" of helpers. It is best to be measured and rewarded in some way to see, if all tune in to the same way of collaboration.

2. Ego and ability to acknowledge own mistakes. It is not infrequent when knowledgeable people will tend to speak up / show off just because they carry the knowledge and may come across as arrogant. The cultural aspect to watch is ego. Less the better for internal communication / collaboration. This way you achieve higher level of inclusiveness -- everyone can learn from each other without mental punishment and is free to impact on larger architectures. Connected with low ego is a rare skill of acknowledging own mistakes. First, it shows that you value learning process. And second, you are human, not a metal-made robot that only improves. You can make a mistake, you are human and can communicate that freely. This shows a great example to peers, that making mistakes is not going to produce a career impacting drama and more -- they can even be rewarded for mistakes, because it is a crucial knowledge bit. Share it on a weekly demo! You may save time for your team.

3. Knowledge sharing sessions. Surprisingly a lot of information flies past engineers, when they are not involved in that particular project. Knowledge sharing sessions are the key. But not only within the team / adjacent departments. Overall on a company level. It is the venue to convey a large message, related to a process update in how tickets are filed or a way to document your component / feature. Or a way to break down a release. Taking first two points -- it is also a way to share some painfully earned bit or a glorious bit of system design, that would not be acknowledged by pretty much anybody unless light is shed on it with good colour.

4. Meaningful meetings. Meetings without prep are time eaters. Save 30 min for a prep-less meeting and ask relevant parties to prep for the next one. If you can avoid a meeting, do! It is way better for an engineer to go read a blog post on some tech / algorithm / system or spend extra time figuring out more test cases for their code. Don't waste their time by asking their statuses, unless it leads to a good discussion. There are other ways to share statuses over work chat for instance. How making meetings a king may kill your culture? People will evade them or use smart phones to mentally "fly away" while the other dude on the team shares a status. If you do such meetings, cap them at 15 min and ask everyone to put down their phones, listen and participate.

5. Culture of retros. Retrospectives (after a milestone or project completion) are a great way to achieve two things: a. Understand and plan on improving what went wrong. b. Release stress after a tough milestone / project. Saying that something needs an improvement in passing over a chat / email / call will lead to 0% positive outcome.

6. Have all folks in the company equally accessible. The early days of a startup enjoy full connectedness. So easy to lean over to a next desk and ask a question -- to everybody. The bigger the company, the harder it becomes: vastly different time zones, narrow focus in teams, "busyness" syndromes. If you are a top manager, take all efforts possible to be available for a chat. It will only help to retain good level of bonding and will help information circulate in the company. Consider it as a constant retraining of your staff. Sharing info in the memos? Might be the only way in triple digit headcount company. But better personal 1-1's.

7. Maintain wide focus. The issue I've seen in IT product companies (can apply to other industries too) is narrowing focus over time. The winning argument is: it helps with velocity of development. But there is a downside too: engineers will tend to narrow down their view of the product and eventually degrade as professionals. Generating ideas of how to improve the product, practicing dogfooding are the gateways to keep engineers motivated, learning and contributing. Roles are great because they identify the responsible drivers of a particular functionality. But getting input and feedback loop from thinkers and tinkerers (engineers) can push the product to new frontiers.


I hope these culture ingredients are useful to consider in your company. What other large cultural aspects you maintain in your company? Feel free to share!