Janea Systems

World-Class Software Engineering on Demand

  • Clients
  • About
  • Team
  • Careers
  • Blog
  • Let’s talk
  • Clients
  • About
  • Team
  • Careers
  • Blog
  • Let’s talk

March of the Machines: Last Month in AI

04.11.2023 by Jamal Robinson

As Bill Gates puts it, the age of AI has indeed begun, and it’s a wild time to be a tech exec. ChatGPT has catapulted AI into the global consciousness and every large organization is racing to manage risks and capture opportunities.

AI’s advancements, in March alone, are quickly changing how we live, work, and interact with the world. NVIDIA CEO, Jensen Huang, emphasized the “sense of urgency for companies to reimagine their products and business models,” OpenAI’s CEO touched on AI’s risks in an interview with ABC News, and a report by Goldman Sachs says it could replace 300 million jobs. For the optimist, we’re embarking on a new era of limitless possibilities. For the pessimist, it might be time to learn a trade.

Software Engineering and Development

March saw the release of over 1000 “AI-powered” products, so it’s clear that software engineers have been pretty busy. While OpenAI’s models continue to be the driving force behind many of these products and the conversation in general, there’s a lot happening at the macro level. Let’s look at some of the key happenings shaping AI last month.

AI Training Costs are Falling

As hardware advances, its cost decreases exponentially. Applying Wright’s Law, Ark Investments forecast that the cost of producing the hardware needed for AI training will fall by 57% annually. Combining the falling costs of hardware with software optimization, they estimate a 70% annual decline in the price of AI training up to 2030. Wright’s Law provides a framework for forecasting cost declines as a function of cumulative production. In this case, it refers to the cumulative output of computational power/hardware that underpins AI training. 

At the same time, competition and improvements within cloud infrastructure continue to break down significant barriers to AI development. For example, Oracle Gen 2 Cloud claims to be faster and cheaper than their competitors, Azure previewed a scalable virtual machine series interconnecting thousands of NVIDIA H100 GPUs at 400 Gb/s to accelerate generative AI, and NVIDIA outlined how they will offer everything from training to deployment for cutting-edge AI services with their partners. These trends meant that competing LLM vendors such as OpenAI, Anthropic, and Cohere could pass on reduced costs to businesses. 

Software optimization is also a major factor in falling costs. Ark Investments estimate that annual neural network software training costs would decline by 47%, and at the start of last month, OpenAI went further. They blew competitors out of the water after the announcement of a public API as well as a 90% cost reduction (before going public, the API was only available to approved users/businesses such as Snapchat) through system-wide software optimization. It’s important to note that these reductions apply to training costs, not operational costs. This dramatic price drop could also potentially be a strategic move to drive early adoption. The public API announcement gave developers direct access to ChatGPT-3.5 early last month. OpenAI then released ChatGPT 4, boasting image understanding, fewer inappropriate/biased responses, and performance advancements.

AI/ML Skills (and Potential Chip) Shortages

With the arms race for AI underway, the field has a significant skills shortage. Machine Learning engineers are in high demand, with some jobs offering over $200k+ salaries for non-management roles. 

Stanford’s AI Index Report cited an increase in AI job postings throughout all sectors, and as companies are rushing to get their AI software to production, there have been many products launched with underwhelming results (*cough* Bard *cough* Ernie).

In March, Microsoft announced they built a supercomputer to power OpenAI’s ChatGPT, while it was also reported that they are rationing access to AI hardware for internal teams. With the Enterprise Artificial Intelligence (AI) Market expected to generate over $50 billion by 2026, there’s trepidation around hardware demand exceeding supply, potentially disrupting the market.

The Future of Software Engineering and Development: Dev Tools 2.0

Towards the end of March, GitHub launched Copilot X utilizing GPT-4. We’re now also starting to see how generative AI will influence software throughout the development lifecycle, as the already widely adopted AI coding assistant can now tag pull requests and answer questions about documentation using an in-editor, ChatGPT-style experience. 

Sequoia’s article on Developer Tools 2.0 and generative AI for software engineering makes predictions for the future and highlights some key players that are revolutionizing the industry. We agree that we will see many Copilot-like tools over the next few years. The article describes potential opportunities outside of “get-help-while-you’re-coding” software, such as software that makes writing code more secure. Coincidentally, on the same day Sequoia published their article, Codium AI released a beta version of their AI-powered code integrity solution called TestGPT. 

AI will have a monumental impact on most industries we work in today and in the future. With the current skills shortage and tens of billions of investments in the field, there’s never been a better time to get into AI and ML.

Transparency and Ethics

Ethical Dilemmas 

Popular communication platform, Discord, launched an AI-powered chatbot last month and simultaneously deleted a clause from its privacy policy that said it wouldn’t store the contents of calls, streams, or channels. Fortunately, consumers noticed, and Discord made a swift U-turn a day later. Following backlash and the reinstatement of their policy, Discord said, “We recognize that when we recently issued adjusted language in our Privacy Policy, we inadvertently confused our users. To be clear, nothing has changed and we have reinserted the language back into our Privacy Policy, along with some additional clarifying information.”

Microsoft has also been in the news after they laid off the ethics and society team that taught employees how to make AI tools responsibly. In a statement, the company said, “Microsoft is committed to developing AI products and experiences safely and responsibly, and does so by investing in people, processes, and partnerships that prioritize this”. They pointed out that they have increased the number of employees working for their Office of Responsible AI and went on to give kudos to the former ethics and society team “We appreciate the trailblazing work the ethics and society team did to help us on our ongoing responsible AI journey.” However, employees highlighted that the ethics and society team ensured that the principles coming from the Office of Responsible AI were actually reflected in the company’s products.

Pausing AI Experiments

At the time of writing, the open letter to pause AI experiments has over 50,000 signatures, including high-profile names such as Yoshua Bengio and Stuart Russell. With AI often framed as an arms race, the open letter proposes a six-month ceasefire to “jointly develop and implement a set of shared safety protocols for advanced AI design and development that are rigorously audited and overseen by independent outside experts.”

Adhering to this open letter would help “humanity  . . .  enjoy a flourishing future with AI.” However, putting this into practice raises concerns over the potential for others countries and institutions to make gains in AI development. China is of particular concern as the country houses 9/10 top institutions publishing AI research, and their government has been accused of cyber espionage and IP theft. 

Realistically, there’s no way of slowing down AI’s advancements. Still, practitioners should think carefully about the ethical implications of developing AI from ideation to data collection through to production.

Black Box AI

Elon Musk, a co-founder of Open AI, criticized the company on Twitter in mid-February:

OpenAI was created as an open source (which is why I named it “Open” AI), non-profit company to serve as a counterweight to Google, but now it has become a closed source, maximum-profit company effectively controlled by Microsoft.

Not what I intended at all.

— Elon Musk (@elonmusk) February 17, 2023

In March 2019, OpenAI LP was created as a “capped-profit” company, with the non-profit OpenAI Inc owning a controlling interest. Four months later, in July, Microsoft invested $1 billion in the LP company and became OpenAI’s “exclusive” cloud computing provider. Despite being open source up to GPT-2, the following installment of GPT-3 became a closed source application. As the majority of large LLMs are closed source, we have to make educated guesses about the inner workings of these tools—researchers and practitioners such as Damien Benveniste, Ph.D. Author of The AiEdge Newsletter and Ex-ML Tech Lead at Meta, outline reasoned hypotheses on GPT-4’s architecture and training.

Microsoft increased its investment to $10bn at the start of this year, and two months later GPT-4 was released on March 14th. It was accompanied by a 98-page introduction paper that boasts its prowess when tested in various professional and academic settings, even passing a simulated Bar Exam with flying colors. Within the “Scope and Limitations” section of the paper, it states:

“Given both the competitive landscape and the safety implications of large-scale models like GPT-4, this report contains no further details about the architecture (including model size), hardware, training compute, dataset construction, training method, or similar.”

In not sharing these details, OpenAI also garnered criticism:

I think we can call it shut on 'Open' AI: the 98 page paper introducing GPT-4 proudly declares that they're disclosing *nothing* about the contents of their training set. pic.twitter.com/dyI4Vf0uL3

— Ben Schmidt / @benmschmidt@vis.social (@benmschmidt) March 14, 2023

Verifying OpenAI’s claim that GPT-4 has fewer inappropriate/biased results without information on its training data is difficult. In the absence of such information, it is not possible to analyze the cause. Only the effect can be observed.

The paper did cherry-pick and highlight some efforts to reduce the harms and biases that GPT-4 can produce.

GPT-4 Technical Report, Page 50 

However, Schmidt goes further in his blog post saying, “Their argument is basically a combination of ‘trust us’ and ‘fine-tuning will fix it all.’ But the way they’ve built corpora in the past shouldn’t inspire trust. When OpenAI launched GPT-2, their brilliant idea was to find ‘high quality’ pages by using Reddit upvotes.”

The paper also references OpenAI research on how they went about red teaming, as well as “A Hazard Analysis Framework for Code Synthesis Large Language Models” which documents hazard severity categories, loss definitions, a risk assessment, and hazard analysis framework for OpenAI’s Codex (the model that powers GitHub’s Copilot).

Balancing individual profit and collective welfare in AI is tough, especially with so much money involved. Even putting aside the money, it’s still extremely challenging to understand the many interconnecting ethical, social, economic, and environmental dimensions of AI while new advancements are being pushed to production as fast as they can be made.

AI for Good 

Despite the doom and gloom, we’ve seen some promising developments in responsible AI in March. Mozilla launched a Responsible AI Challenge where entrepreneurs and AI builders creating ethical and holistic AI can win up to $25,000. They also released a research paper on AI Transparency in Practice in conjunction with ThoughtWorks.

The Ada Lovelace Institution published a discussion paper analyzing the EU’s 2021 AI Act and its defined technical standards. The report identifies a regulatory gap between the EU’s standardization policy (the process by which the European Union develops and adopts consistent technical standards) and the AI Act, raising concerns about the protection of fundamental rights. 

The paper states:

“If neither the legislative text of the AI Act nor standards clarify how to comply with the AI Act’s essential requirements for fundamental rights and other public interests, AI designers may not implement them effectively, leaving the public unprotected.”

It suggests policy strategies to increase civil society participation, and enhance democratic control over essential requirements, ultimately reinforcing the AI governance framework.

Politics, Policy, and Law

With AI often being rushed to production, we’ve seen governments and lawmakers worldwide both embrace and grapple with AI.

At the end of last month, Italy’s data-protection regulator banned ChatGPT in the country, citing privacy concerns. The ban followed an outage that exposed users’ conversations and payment information on March 20th. The regulator said “the mass collection and storage of personal data for the purpose of ‘training’ the algorithms underlying the operation of the platform” had no legal basis and also touched on the fact that there aren’t any tools in place to verify the age of the platform’s users. They gave OpenAI 20 days to respond to how it plans to address their concerns. Other regulators like the Irish Data Protection commission and the consumer advocacy group BEUC have echoed similar sentiments. ChatGPT is already blocked in several countries, such as China, North Korea, and Russia (although there are other geopolitical complexities to consider in these cases). 

The UK Chancellor, Jeremy Hunt, announced that the government will launch an “AI sandbox” to encourage research into artificial intelligence. With aims for the country to become a “science and technology superpower” the government plans to launch a £2.5bn into quantum computing. However, the country’s legislation on AI has been scrutinized for not ensuring that the use of AI is safe and ethical in the long term.

The U.S. Chamber of Commerce published an Artificial Intelligence Commission Report last month. They claim that “over the next 10 to 20 years, virtually every business and government agency will use AI. ” and highlight issues around potential harms to individual rights. Promoting responsible AI is a top priority for the U.S. government, but with the speed at which AI is progressing, it won’t be an easy feat.

Last month, the U.S. Copyright Office also officialized a landmark authorship policy regarding generative AI. The policy stipulates the grounds under which AI-generated work can be copyrighted; “whether the ‘work’ is basically one of human authorship, with the computer [or other device] merely being an assisting instrument, or whether the traditional elements of authorship in the work (literary, artistic, or musical expression or elements of selection, arrangement, etc.) were actually conceived and executed not by man but by a machine.” Although there is bound to be much deliberation over the degree to which AI is used as an “assistive instrument” or not, it’s a great starting point.

The Romanian Prime Minister unveiled an AI “adviser”, telling him what people think in real-time. Named Ion (the Romanian equivalent of John), the AI system “will use technology and artificial intelligence to capture opinions in society” using “data publicly available on social networks,” according to a government document detailing the project. Autonomous social media monitoring used by a head of state could make some feel rather uneasy, especially considering the abovementioned biases. 

As in most cases, policy needs to catch up to technological advancement. What’s more interesting is how governments utilize AI technology in day-to-day work, such as in the case of the Romanian Prime Minister.   

Pharma, Healthcare, and Life Sciences

We know that AI will continue to disrupt almost every industry, but the beginning of AI within Pharma, Healthcare, and Life Sciences is particularly promising. 

Last month we saw a research article by Lin and colleagues describing the creation of a transformer language model capable of predicting hundreds of millions of protein structures. This groundbreaking work can help us better understand life itself and develop new applications in medicine, agriculture, and many other fields. This represents a potential advancement over AlphaFold, a model which has predicted the shape of 200 million proteins. To put both of these in perspective, we’d been able to map approximately 100 thousand proteins in the preceding 50 years of study.

The National Institute for Health and Care Research (NIHR) is contributing over £1 million pounds to develop AI to cherry-pick organs for transplants. The new deep learning, computer vision model known as Organ Quality Assessment (OrQA) “will be trained using thousands of images of human organs to assess images of donor organs more effectively than what the human eye can see.” OrQA aims to allow surgeons to take a picture of an organ, upload it to OrQA and receive immediate feedback on how it should best be used. It is estimated the technology could help up to 200 more patients receive kidney transplants, and 100 more receive liver transplants every year in the UK.

With prolific advancements in the field, the FDA also issued a re­quest for in­for­ma­tion on  Artificial Intelligence in Drug Manufacturing last month alongside a discussion paper containing eight questions. Some of the questions include:

  • What types of AI applications do you envision being used in pharmaceutical manufacturing? 
  • Are there additional aspects of the current regulatory framework (e.g., aspects not listed above) that may affect the implementation of AI in drug manufacturing and should be considered by FDA? 
  • Would guidance in the area of AI in drug manufacturing be beneficial? If so, what aspects of AI technology should be considered?

From these questions, CDER and the FDA hope to consider the application of “its risk-based regulatory framework to the use of AI technologies in drug manufacturing.” The deadline for submitting responses is May 1st.

Finance

Finance has been using AI at scale for longer than almost any other industry. As early as the 1990s, AI has been used to estimate credit risk, support portfolio management, and automate trading. Early comments from the industry on the future of AI in Finance, such as those from the deVere Group CEO, seem to indicate more of the same but with increased sophistication and scale. He said,

“AI chatbots and virtual assistants can help financial institutions offer personalized customer service, 24/7, and respond to client queries in real-time. It could also help financial institutions discover fraudulent activities by analyzing large amounts of data in real-time and identifying unusual behaviour trends. As such, this will help financial institutions make better and faster decisions by analyzing facts and figures and providing insights into potential opportunities or risks.” 


After offering ChatGPT subscriptions in mid-February, OpenAI announced that Stripe will be powering ChatGPT Plus payments, and that GPT-4 will be used to build AI tools for Stripe. Stripe has already employed AI to help manage fraud and increase conversion rates, but they have also explored how GPT-4 can streamline operations. One of the first enhancements announced is GPT-powered Stripe Docs, allowing developers to ask questions about Stripe documentation and get relevant answers.

Security

Let’s start with some good news. The US Transportation Security Administration (TSA) is using AI to reduce unnecessary pat-downs. Designed to ease the passenger airport process for transgender and nonbinary travelers, the AI algorithm for body scanners has been rolling out for the past few months. The TSA attributes the updated algorithm to the shrinking number of pat-downs reported. Previous technology relied heavily on gender binary to determine whether passengers could be hiding contraband. After recognizing a trend of false alarms, an algorithm update was deployed to over 1000 Advanced Imaging Technology units “to significantly reduce false alarms” says R. Carter Langston, a TSA spokesperson.

Less good news is the emergence of AI-powered fraud. A couple in Houston claim they have been scammed out of $5000 after thieves used AI to clone their son’s voice. The couple reports that phone scammers impersonated their son and falsely claimed to have been in a car accident involving a pregnant woman.

OpenAI’s CEO touched on the risks of the platform during an ABC News interview, saying, “I’m particularly worried that these models could be used for large-scale disinformation. Now that they’re getting better at writing computer code, [they] could be used for offensive cyber-attacks.” 

The UK National Cyber Security Centre: published a blog outlining the risks of ChatGPT and large language models. The blog highlights concerns that LLMs might “learn” from your prompts and offer that information to others who query related things. It also touches on the risk of companies with less robust privacy policies acquiring LLMs and taking a different approach to user privacy. Posted six days before ChatGPT malfunctioned, it highlighted the risk of queries stored online being “hacked, leaked, or more likely accidentally made publicly accessible.” 

We’ve seen how AI can be leveraged for malicious purposes, taking AI tools and adapting them to deceive and gain access to external systems. We’ve also seen how malfunctions can cause security issues, such as leaking private information. What’s more worrying is the potential for bad actors and attackers to infiltrate the inner workings of AI systems themselves.

Oprea A and Vassilev A produced a paper called Adversarial Machine Learning: A Taxonomy and Terminology of Attacks and Mitigations for the US National Institute of Standards and Technology last month. It introduces and expands on various concepts that attackers and bad actors could use to compromise AI systems, such as; availability breakdown, integrity violations, and privacy compromise. The paper’s goal is to “create a standard terminology for adversarial attacks on ML that unifies existing work.”

Adversarial Machine Learning will undoubtedly be a critical field as we enter the age of AI, especially following the ChatGPT outage/malfunction on March 20th.

In Conclusion

Despite the length of this article, it is by no means an exhaustive roundup. Frankly, at the pace AI technologies are advancing, there’s too much to cover. Although we’ve highlighted more of the bleaker aspects of AI from last month, here at Janea, we truly believe that AI can create a positive and long-lasting impact on the world. Having seen and worked on AI projects that continue to revolutionize the way we live (such as PyTorch), we’re confident that the benefits of AI far outweigh the challenges. As we continue to build on our AI practice, we focus on responsible development, careful consideration of ethical implications, and collaboration between diverse experts to help develop AI technologies that empower humanity.

To learn more about our work in Artificial Intelligence, contact us here.

Filed Under: AI & Machine Learning Tagged With: AI & Machine Learning

Share Us

Facebook
fb-share-icon
Twitter
Tweet
LinkedIn
Share

Sign Up for our Newsletter

Follow Us

113 Cherry Street #11630, Seattle, WA 98104

  • Privacy
  • Cookies

© 2023 All rights reserved

Mike DeCerbo

Chief Operating Officer

michaeldecerbo

As Chief Operating Officer for Janea Systems, Mike is responsible for overseeing the day-to-day administrative and operational functions of the business. He brings more than 20 years of experience to Janea Systems. His experience and leadership have been focused on developing and delivering consulting services and software solutions, building high-performing teams, and driving efficiency in large scale global operations.

Prior to joining Janea Systems, Mike was the Vice President of Business Operations for the Technology Services division of Altisource, a leading provider of services and technology to the mortgage and real estate industries.   There he was responsible for a wide variety of functions for the technology organization including financial management, process improvement, commercials management, performance management, Business Intelligence, strategic initiatives, and leading a professional services team providing custom development and business consulting services.  Before that, Mike ran the professional services organization at Oco, a developer and provider of cloud-based business intelligence (BI), analytics, and data integration solutions, which was eventually acquired by Deloitte.  Earlier in his career, Mike worked at a number of consulting firms, including Deloitte Consulting, delivering technology consulting services across a variety of domains and industries.

Mike holds a B.S. in Biomedical Engineering from Rensselaer Polytechnic Institute. Originally from Connecticut, Mike now lives outside Boston in Natick with his wife and 3 young children.

Toby Rawlinson

Senior Vice President of Sales

tobyrawlinson

Prior to joining the Janea Systems team, Toby held positions with Aditi Consulting as VP of Engineering Consulting Services, Akvelon Inc. as Director of Growth & Strategic Accounts, Head of Consulting & Business Development for ProZone Sports (UK) in the sports analytics & emerging tech space, as well as lecturing & coaching in the United Kingdom & U.S.

Most recently, Toby was a key member in securing sustained growth in both revenue and client acquisition. Developed & built engineering & project-based consulting success, serving clients such as Microsoft, Goldman Sachs, Seattle Seahawks,Reddit, Doordash, F5 Networks, Qualtrics, Maana and more.Toby also held consultancy roles with FIFA, UEFA, the Welsh National Team, Chelsea, Arsenal, Ajax and Juventus.

Before relocating to the U.S, Toby lectured and taught at both the University of Worcester and Worcester Sixth Form College in the UK. He focused his time on delivering the Sports & Exercise Science, Sports Performance analysis curriculum and running the Worcester 6th Form Football Academy.

Toby has a MSc. in Education & a BSc. (Hons) in Sports & Exercise Science, as well as holding several national coaching qualifications including the UEFA ‘B’ football License.

Alexis Campailla

Chief Executive Officer

alexisca

Alexis founded Janea Systems out of his passion for software engineering and solving complex technical challenges.His calling for math, science and programming was apparent from a very early age. At age 9 he started learning how to code on a Commodore 64 and within months he was already programming games in assembly language. Before graduating from high school he was proficient in C and was dabbling in graphics driver development for the IBM PC. After graduating cum laude at the university of Rome, where he also won several high-profile programming competitions, he moved to the USA after being headhunted by Microsoft, where he was part of the team that created the first version of the .NET Runtime. During his time at Microsoft he was awarded numerous patents and various publications including: “Efficient filtering in pub/sub systems”. After participating in the first 2 major releases of .NET, he left Microsoft to co-found Wishpot – a startup aimed at creating universal wishlists, later acquired by Light in the Box – where he was CTO.

Microsoft then sought his services as a consultant to help solve some of their deepest technical challenges, working on .NET, Windows, Exchange, experimental projects for the office of the CTO, and leading several high-impact open source projects for MS Open Tech. This included the Node.js on Windows initiative where he became a member of the Node.js Foundation’s technical governing body, the Technical Steering Committee. He also led the Redis  on Windows project and oversaw the creation of Memurai, from the go to market strategy, and deep involvement in delivering the code for the product’s core features and improvements.

Coupled with a passion and experience in software engineering, knowing very well that the world is being eaten by software and yet a seemingly endless shortage of engineering talent, motivated him to find innovative ways to connect the best talent to the most challenging demands of the industry worldwide. Eventually leading him to recruit more like-minded people and build a team of engineering excellence at Janea Systems, where he now serves as CEO.

In his free time, he enjoys playing beach volleyball, playing music, and travelling.

Elias Najjar

Lead Software Engineer

Elias Najjar is a Lead Software Engineer at Janea Systems, where he oversees the development and maintenance of QCash Financial’s loan decision engine platform. He is a solution-driven engineer with over 11 years of experience building robust, user-focused software.

Elias is well-versed in all phases of the software development lifecycle and has substantial expertise in translating business requirements into technical solutions.

Before joining Janea, Elias was a project manager at PlanB Solutions, where he hired and led a remote team of 8 developers. Throughout his career, he has completed several notable projects, including an Eikon App Studio Application for Thomson Reuters and the PBS Galaxy ERP system, which consisted of several modules such as CRM, lead management, and accounting.

Elias graduated with an M.S. in Electrical & Computer Engineering from the American University of Beirut in Lebanon. 

Sergio Dominici

Head of Engineering Delivery

Sergio is the Head of Engineering Delivery at Janea, where he oversees a team of 40 engineers. With 25 years of experience in IT, Sergio has worked on several groundbreaking projects including; the development of a collaborative online editing platform, a 3D incident command training simulator, and a wide area measurement system for a national transmission system operator.

Prior to Janea, he worked in various roles such as consultant, project manager, product manager, IT manager, and CTO in a number of different industries. 

Sergio graduated in Computer Science Engineering in Italy and currently lives in Spain. In his spare time, he enjoys playing the guitar, bass, and piano, baking pizza, and riding his motorbike. 

Zak Greant

VP of Strategy

Zak Greant serves as the Vice President of Strategy at Janea Systems and the General Manager for Memurai, the company’s product division. Their career has been dedicated to helping open source startups and non-profits flourish. Initially focused on software development, open source advocacy, and marketing, they eventually transitioned to strategy and leadership roles.

Over the past 30 years, Zak has contributed to software, projects, and licenses used by a majority of the world’s developers. They have worked with prominent organizations such as the PHP project, MySQL AB, the Mozilla Foundation, the Open Source Initiative, ActiveState, and the Free Software Foundation. 

SharePoint

Worked on the client components of Microsoft SharePoint. The client code also shipped with Office XP. Responsible for the core architecture of the project. The architecture allowed integrating of SharePoint Portal with the Windows Shell and Office and supported different servers 

.NET Framework

Participated in the design of a messaging protocol system for the .Net Platform & later SQL Server. 

  • The system design provided sync/async messaging with quality-of-service, queuing, and integration of multiple protocols and devices. 
  • Responsible for the pub/sub functionality of the project. 
  • Completed research in the field of the inverse query problem. 
  • Invented original algorithms for the filtering problem, for which two patents were acquired. 

arm Compiler

Supporting the C/C++Compiler for ARM team: 

  • Implemented and optimized the ARM Thumb-2 code generation in the C/C++ compiler and micro-architecture optimizations for Qualcomm ARM chips. 
  • Implemented the code generation of Pogo for ARM and experimented with Travel Time Debugging for ARM. 
  • Proposed and made an ARM specific implementation of basic block reordering in the ARM compiler. 35% working set reduction and 20% page load reduction in IE. 29% code size reduction over 32bit ARM.

Zune

Janea Systems developed various features for Microsoft’s digital media products: 

  • Zune.net website, including the Silverlight video player. 
  • Ported the service to Windows and 64-bit. 
  • Deployed automation and other process improvements. 
  • Architected storage and management of high-business-impact security-sensitive data. 
  • Architected features for the integration with Bing. 

Expedia

Developed the Lodging “Price and Availability Engine”, which servers over 300 million requests per day and is key to Expedia’ success. 

  • Designed and implemented key C++ components in the large scale data flow that feeds the server caches, including a superb lock-free hashtable that could process 5million products per second (per box). 
  • Designed & built the ETL data pipes and cloud processes to collect and analyze corporate brand data. We used Apache Spark, S3, Redshift, DynamoDB, Kafka, Spark Streams and much more. 
  • Designed the creation of Spark jobs that could re-process 2 years of data in a couple of hours, running in 450 cloud nodes. 

LLVM C++

Integration of CLANG FE with VSC++ compiler development. Supporting the integration of CLANG with VS C++ code generation used to build & compile for frameworks and Runtimes. 

Microsoft Teams

Provided engineering support (Node.js & Electron) to the TEAMS engineering group to improve start-up performance by 20%. 

Microsoft Azure

 Supporting the development of AzureX-Plat SDKs & Developer tooling. 

Memurai

Memurai – Our very own Redis-compatible cache and datastore for Windows. Memurai originated from our work leading the Redis on Windows project for MSOpenTech. memurai.com  

Node.js for Windows

Managing the Windows version of Node.js on behalf of Microsoft, from 2013 to present day. github. com/nodejs/node 

.NET Common Language

Development of the .NET Common Language Runtime, particularly in the areas of portability, garbage collection and performance. 

Benedetto Proietti

Head of Memurai

benedettoproiettimathematician

Benedetto has a 20+ years of computer software engineering and programing experience ranging from being a Principal engineer in a Fortune 500 software centric companies to designing and building a custom supercomputer (in Italy with International Institute for Nuclear Physics, in Germany with DESY) to analyse and simulate quark interactions.

He has extensive experience with massive production distributed systems as well as tools development such as C++ compilers and tools. Benedetto has frequently designed and developed novel computer algorithms to solve computer vision, acoustic & subsea imaging, road traffic and performance related problems.

Currently Benedetto leads the Memurai division of Janea Systems trying to diversify the product offering, build deterministic marketing and sales machines, and grow a top notch engineering team. In his spare time, Benedetto has fun with FPGA designs, in memory engines (take a look at his MemFusion project), and functional programming.

Benedetto has also been a National Mathematics finalist at the International Mathematical Olympiad and presented his thesis with INFN at the University of Rome “La Sapienza”  on extending C/C++ for a SIMD machine and porting GNU compilers for APEmille supercomputer.

Filip Proborszcz

Engineering – Developer

filip-proborszcz-38844340

Having competed in several programming contests & Olympiads, Filip started his engineering path in his early school years. He went through a variety of projects like Lego Mindstorm robot contests, ubiquitous computing rotten tomato social experiment, Web graph compression with fast access algorithms, and many more requiring interpersonal skills and intuition.

When it comes to specific projects, Filip created and maintained several core Web services mainly used by mobile apps like city guides or lotteries for a company in Spain, developed a complex backend for an online shop in Barcelona, and even helped to implement a staff management system at a bus factory Solaris in Poland. Later he joined Intel and worked on Windows kernel drivers for Intel’s audio proprietary HW solutions.

Filip not only loves to hear from clients, but also appreciates listening to some good music and even being part of it by singing in a choir “Music Everywhere”, performing on stage, playing violin, drums, or guitars.

Enterprise Open Source Software development & strategy

No matter how smart people are you hire inside your company, there’s always smarter people outside”

Our team’s extensive experience being trusted by our clients to develop, manage, contribute and execute their mission critical OpenSource projects and technology initiatives (Node.js, Node.js Mobile,  React Native, PowerToys, MSOpenTech, Redis port to Windows) spans several years and is a key contributor to supporting their successful products and services delivery. Benefits we have realized include;

  • Innovating faster.
  • Achieving quicker time to market.
  • Collecting new ideas & offset knowledge gap.
  • Enabling interoperability or de facto standards.
  • Gathering diverse viewpoints and contributions to produce better code and better products.

Project “Thali”

Project ‘Thali’ an open source peer to peer enabled web framework to provide distributed identity, privacy centric discovery, built in synchronization, support for Cell, Wifi, BLE, Bluetooth and the iOS Multi-Peer Connectivity Framework, all built on Node on Android and iOS to let devices collaborate regardless of what kind of Internet infrastructure is available.

Node NPM

Janea Systems introduced a new way of writing files in Node.js using a memory file mapping, which can be several times faster under some circumstances. This is already in use by node-tar (https://www.npmjs.com/package/tar) and is planned to be picked up by npm on version 7. On npm, this can mean up to 50% faster execution time when the right conditions are met.

Chakra Core

Supported the Javascript runtime “Chakra” team that powers Microsoft Edge and Node+Chakracore (JS Engine) Worked on Unicode/Intl library of Chakra engine. Worked on implementation of Javascript language features and with porting “Node. js” to Chakra engine and active contributors and maintainers of the project. Worked on performance improvement of Node+Chakracore. Debugging activities included but not limited to debugging memory leaks, native machine code, performance regression, etc.

Azure CLI

Contributing to the development of the Azure Cross-Platform Command Line Interface (CLI) experience for developers managing Azure resources.

Node.js to iOS and Android

Our port of Node.js to iOS and Android.
code.janeasystems.com/nodejs-mobile

Microsoft Open Technologies

Janea Systems enabled core interoperability scenarios between Microsoft and Open Source technologies, spanning developer tools (Azure, Linux, Java, Python), plug-ins, SDK’s to big data, cloud interop & web.

React Native

React Native for Windows – Development of native modules to run platform specific code for Windows on behalf of Microsoft.

PowerToys for Microsoft

The recently reinvented Microsoft PowerToys system utilities.github.com/microsoft/ Power Toys

Jaime Bernardo

Engineering – Lead Developer

Jaime is a senior software engineer with a diverse engineering background, having worked on management software, mobile, game and tools development covering many industry verticals with over 10+ years of experience.

Jaime has had a passion for programming since he self-taught how to program at the age of 11 and has since then refined this passion into algorithms, low-level and system code. He loves tackling difficult bugs where he has to go deep to solve them, treating them as elaborated and satisfying puzzles.

Jaime’s project work for Janea Systems covers many areas including porting Node.js to Android and iOS, porting react-native modules to Windows, porting the Azure Maps SDK to iOS and developing the first PowerToys versions, among other projects

In his free time, he enjoys reading about philosophy, politics and economics and playing board and video games.

Microsoft Consulting Services

Defined, architected & delivered common standards for a Web Services architecture to support & handle MPS (Bank Consortium) migration to X-Platform open protocols for security, transactions, reliability & more. Developed extensions to implement support for certs, digital signatures, session management etc.

João Reis

Engineering – Lead Developer

joaocgreis

João was part of a robotic soccer team implementing scientific progress and innovation in cognitive systems and Robotics applications at the Intelligent Robots and Systems Laboratory (IRS Group), while studying for his computer engineering degree. João joined Janea Systems in April 2015, working from Portugal.

He coordinated software development and was responsible for the ROS based middleware at RoCKIn. After graduating he worked on robotics research for several years as a software engineer.

After joining Janea Systems, he worked on maintaining the Windows version of Node.js, including the development and maintenance of the Windows CI system in close collaboration with the open source community. João also worked on several cloud agnostic projects, giving him deep experience and ability to work across the board, from embedded to massive web applications.

João likes learning better tools to make new things, solving problems that make a difference and making the quality of the final solution his first priority.

Dragoș Dăian

Engineering – Developer

dragos-daian-aa29b7a7

Dragos has several years of experience as a software engineer working mainly with C++ on complex projects ranging from navigation (in NDS format) to web services for data streaming, documenting the API with OpenAPI. He is also well versed in the Boost libraries and language standards.

He has extensive experience with Continuous Integration Systems such as Jenkins and Github Actions. When it comes to testing experience, he worked with GTest and Docker for the environment.

During high school, he attended the National Olympiad of Informatics, as well as building and working on many small games and other projects in C++, later building in his free time games using Unity 3D, using C# as a scripting language.

In his free time, he really enjoys playing basketball outside and meeting new people this way. Currently living in the Netherlands, he likes to go on bike rides.

MSDN

Janea Systems architected and managed the transition of the Microsoft Developer Network subscriptions services to Azure.

Modern web technologies (server & client side).

Deep web-tech is where our team has a lot of fun. An exceptionally deep background across this area includes expertise building large scale, fully distributed web applications as well as experience building JavaScript Engines, runtimes (Node & Deno), JS interpreters and JIT Compilers. We have been trusted to port React Native modules (iOS & Android) to Windows on behalf of Microsoft.

SQL Server Team

SQL Server Team – Developed pub/sub functionality & designed highly scalable filtering engine for high-message volumes.

Microsoft Consulting Services

Supporting Microsoft Consulting Services – Designed, architected and managed the development of a $25M system to support real time data collection for the Italian Railway Network across all control stations.

Bing

Janea Systems developed a set of C++ classes that dramatically improved the development time of test cases for the Microsoft Search engine.

Exchange Server

Janea Systems helped architect & prototype new features for Exchange Server. Leading the task-force for the CTO to design new (SSE) for RSS.

Viasat Technology

An R&D software project to monitor road traffic (firmware + GPS Windows simulator). The firmware in the car sends the GPS positions via SMS to Viasat data-center. This software has been released with ISO 9001 quality documentation.

Mono

Development on Mono project, including the native runtime, JIT (just-in-time) and AOT (ahead-of-time) compilers, and .NET class libraries. Responsible for porting Mono runtime and class libraries to Apple Watch platform, including initial port of the JIT to ARMv7k architecture and LLVM bitcode mode.

LLVM

LLVM, a toolkit for the construction of highly optimized compilers, optimizers, and run-time environments. Contributed initial support for Win64 exception handling, including extension of the objdump tool to support output of the Windows exception tables on object files. COFF relocation fixes to the COFF object emitter. Held commit rights in the LLVM project.

Flood 3D Game Engine & Toolset

Flood was an hybrid C++ / C# game engine and toolset. Responsible for initial idea, design and implementation of the C++ core classes, graphical engine and editing tools. Also designed and implemented a distributed network remoting system for syncing object state between different machines.

Xamarin

  • Responsible for creating and developing the CppSharp project. CppSharp will take a bunch of user-provided C/C++ headers and generate either C++/CLI or C# code that can be compiled into a regular .NET assembly. Using itto develop integration bindings for PS4 and BlackBerry platforms with Xamarin platform.
  • Responsible for maintenance and development of Xamarin.Android platform integration with .NET runtimes.
  • Responsible for continued class library bug fixing and development, including development of System.IO. compression libraries.

Path Scale

A world leader in subsea acoustic imaging sonars. Architected and implemented new software & designed novel computer vision algorithms to solve specific acoustic imaging problems:

  • Background Subtraction algorithm for subsea imaging sonars
  • Super-resolution mosaic: the objective to generate one super-resolution image from a sequence of a low resolution images. Running on the GPU at 100 frames per second.
  • Built kinematic model Semi-automatic fish counting. Improved the statistical approach of George Cronkite to work with variable fish densities and reduced sampling.

Wilderness Lab

Engineering product development at Wilderness Labs, including:

  • Porting the Mono .NET runtime to the NuttX RTOS.
  • Continued feature and bug fixing work around microcontroller and operating system
  • Implemented new Mono AOT compilation backend for ARM Thumb, based on LLVM framework.
  • Implemented new STM32 F7 machine, based on Cortex-M architecture on QEMU, including QSPI emulation, along other peripherals.

Power BI Report Server

In January 2018, Google announced that the final release of AngularJS would be 1.7 and would enter Long Term Support. The PBI Report Server team needed support to migrate the portal from Angular.

Skype

Providing Node.js engineering support & consultancy to the Skype ‘service’ engineering team to re-architect server-side components of the Skype connection manager.

Windows Terminal

Supported the Windows Terminal team to improve the Windows Command Line experience for developers.

Microsoft Visual C++

Supported the Visual Studio Compiler Backend and Linker team. Responsible for the 64-bit Linker quality.

Common Data Service

Supported the CDM team. Responsibilities included adding functionality and refactoring, including restructuring tests.

SQL Server Team

Italian Institute of for Nuclear Physics & DESY.
Ported GCC C and C++ compilers to APEmille parallel supercomputer, a joint project of INFN and DESY.

INFN & DESY

Italian Institute of for Nuclear Physics & DESY.

  • Ported GCC C and C++ compilers to APEmille parallel supercomputer, a joint project of INFN and DESY.
  • Working in the LQCD (Lattice Quantum Chromo Dynamics) field using supercomputers to simulate quark interactions. Compiler generated the fastest code among the pre-existing compilers for APEmille.

Power Toys for Microsoft

Project Thali, a partnership between Rockwell Automation and Microsoft to enable peer to-peer communication and synchronization between devices on the factory floor.

Device driver & kernel development.

Whether you need specialized drivers development for Windows, Linux, or other OSs, Janea Systems has the experience to create robust and highly optimized device drivers for your custom hardware.

IoT, embedded and firmware development.

Our experience spans building custom real-time embedded software, debuggers, bootloaders, low level software frameworks & more. We’ve supported development of products in a wide range of industries including automotive, consumer electronics, defense, industrial, medical and space systems.

Big data and database development.

Our team’s expertise in building big data & DB back-end solutions is unmatched, with a team of experienced and tenured architects and developers. We have successfully built our own In-Memory DB solution Memurai, which is trusted and used by clients (Department of Defense (US Air Force), Deutsche Telecom, HPE, etc.) worldwide, helped our enterprise clients architect and build custom solutions to support their in house products and services and contributed to building enterprise grade DB’s such as SQL Server and more…how can we help you?

Developer tools, frameworks & platforms.

Our team’s origins stem from a heritage of building systems-level software development tools (OS’s, API’s, SDK’s, CLR, CLI, Custom Tools (De-buggers, Code Editors, IDE’s) etc.) for enterprise developers, ranging from closed source to Open Source. We have helped the most software centric companies build tools to improve and optimize engineering efficiency, productivity and velocity across various OS’s and platforms.

Janea Systems

  • Clients
  • About
  • Team
  • Careers
  • Blog
  • Let’s talk