A Tshwane computer engineer has tracked down one of the great treasures of the computer age – the first space flight guidance computer. ARTHUR GOLDSTUCK tells the story.
It’s not often that a YouTube video on a technical topic gives one goosebumps. And it’s not often that someone unpacking a computer makes history.
Francois Rautenbach, a computer hardware and software engineer from Tshwane, achieves both with a series of videos he has quietly posted on YouTube.
It shows the “unboxing” of a batch of computer modules that had been found in a pile of scrap metal 40 years ago and kept in storage ever since. Painstaking gathering of a wide range of evidence, from documents to archived films, had convinced Rautenbach he had tracked down the very first Guidance and Navigation Control computer, used on a test flight of the Saturn 1B rocket and the Apollo Command and Service Modules.
Apollo-Saturn 202, or Flight AS-202, as it was officially called, was the first to use an onboard computer – the same model that would eventually take Apollo 11 to the moon. Rautenbach argues that the computer on AS-202 was also the world’s first microcomputer. That title has been claimed for several computers made in later years, from the Datapoint 2200 built by CTC in 1970 to the Altair 8800 designed in 1974. The AS-202 flight computer goes back to the middle of the previous decade.
His video succinctly introduces the story: “On 25th August 1966, a very special computer was launched into space onboard Apollo flight AS-202. This was the first computer to use integrated circuits and the first release of the computer that took the astronauts to the moon. Until recently, the software for the Block 1 ACG (Apollo Guidance Computer) was thought to be lost…”
One can be forgiven for being sceptical, then, when he appears on screen for the first time to say, “I’ve got here with me the software for the first microcomputer.”
Then he unwraps the first package and says: “Guys, these modules contain the software for the first microcomputer that was ever built, that was ever used.”
The goosebumps moment comes when he reveals the NASA serial number on a device called a Rope Memory Module, and declares: “These modules are the authentic flight AS-202 software modules. These were found on a rubbish dump, on a scrap metal heap, about 40 years ago … and we are going to extract the software from this module.”
In a series of three videos, he extracts the software, shows how the computer was constructed, and uses a hospital X-Ray machine to inspect its insides. The third video starts with the kind of phrase that often sets off the hoax-detectors in social media: “Okay, so you guys won’t believe what I’ve been doing today.” But, in this case, it is almost unbelievable as Rautenbach takes the viewer through a physical inspection of the first Apollo guidance computer.
How did an engineer from Tshwane stumble upon one of the great treasures of the computer age? He has tended to avoid the limelight, and describes himself as “a hardware/software engineer who loves working on high-velocity projects and leading small teams of motivated individuals”.
In an interview this week, he added: “I am the perpetual hacker always looking for a new challenge or problem to solve. I have experience in designing digital hardware and writing everything from embedded firmware to high level security systems. Much of the work I did over the last five years revolved around building new and creative payment solutions.”
The breadth of his work gave him the expertise to investigate, verify, and extract the magic contained in the AS-202 computer. A global network of contacts led him to the forgotten hardware, and that is when the quest began in earnest.
“I got interested in the Apollo Guidance Computer after reading a book by Frank O’Brien (The Apollo Guidance Computer: Architecture and Operation). Most of us grew up with the fallacy that the AGC was less powerful than a basic programmable calculator. I discovered that this was far from the truth and that the AGC was in fact a very powerful and capable computer.
“I started communicating with experts in the field and soon realised that there was a wealth of information available on the AGC and the Apollo space program in general.
“One day I received some photos of AGC Rope Memory modules from a friend in Houston marked ‘Flight 202’. After a little googling, I realised that these modules contained the software from Flight AS-202. As I learned more about AS-202, I discovered that this was the first time the AGC was used in an actual flight.”
Rautenbach eventually tracked down the source of the photos: a man who had picked up the entire computer, with memory modules, at an auction, as part of a three-ton lot of scrap metal.
“At one point he opened up to me and said he had other modules. He admitted he had a full Apollo guidance computer, and my theory was that it was used to develop the Apollo 11 guidance computer. He sent me more information, and I thought he had THE computer.
“He’s got all this junk in his backyard. He started selling stuff on eBay and one day got a visit from the FBI wanting to know where he got it. He was able to find the original invoice and showed it to them and they went away. But it scared him and he didn’t want to tell anyone else in the USA what he had. Not being from America was an advantage.”
Rautenbach flew to Houston last year, opened the sealed packages and filmed the process.
“This was the first microcomputer. I opened it and played with it. I realised this was the first computer that actually flew. I also found Rope Memory modules that said Flight 202, and he didn’t know what that was. I found it was from AS-202, and I said we can extract stuff from this.”
Rautenbach paid a deposit to borrow the units and have them sent to South Africa, so that he could extract and rebuild the software. He also made contact with Eldon Hall, leader of the team that developed the Apollo guidance computer and author of the 1966 book, Journey to the Moon: The History of the Apollo Guidance Computer.
The correspondence helped him verify the nature of the “scrap”. The Apollo command module from flight AS-202 was restored and is now on permanent display on the USS Hornet, the legendary aircraft carrier used to recover many Apollo command modules and now a museum. However, the computer parts were sold as scrap in 1976. And NASA never preserved a single copy of the software that had been used on its first guidance computer.
Fortunately, a sharp-eyed speculator realised the lot may contain something special. He sold off some of the scrap over the years, until that visit by the FBI. He still prefers to remain nameless.
Last week, on the 50th anniversary of the launch of AS-202, Rautenbach quietly began posting the evidence online. He also announced that the raw data he had extracted would shortly be made available to anyone who wished to analyse it.
His videos on the unboxing of the AS-202 computer and the extraction of the software can be viewed on YouTube at http://bit.ly/as202, where he also plans to post instructions for accessing the software.
- Arthur Goldstuck is founder of World Wide Worx and editor-in-chief of Gadget.co.za. Follow him on Twitter and Instagram on @art2gee
Nasa’s description of flight AS-202 can be found at: http://nssdc.gsfc.nasa.gov/nmc/spacecraftDisplay.do?id=APST202
Technical specifications of the Apollo Guidance Computer can be found at: https://en.wikipedia.org/wiki/Apollo_Guidance_Computer
Apollo comes back to Pretoria
Francois Rautenbach points out that South Africa played a prominent role during the 93 minutes of flight AS-202: “Pretoria is mentioned no less than three times in the post-flight report. The AS-202 flight actually reached it’s highest point above South Africa. The telemetry data from the flight were recorded on computer tape at Hartebeesthoek and later shipped back to NASA.”
Now IBM’s Watson joins IoT revolution in agriculture
Global expansion of the Watson Decision Platform taps into AI, weather and IoT data to boost production
IBM has announced the global expansion of Watson Decision Platform for Agriculture, with AI technology tailored for new crops and specific regions to help feed a growing population. For the first time, IBM is providing a global agriculture solution that combines predictive technology with data from The Weather Company, an IBM Business, and IoT data to help give farmers around the world greater insights about planning, ploughing, planting, spraying and harvesting.
By 2050, the world will need to feed two billion more people without an increase in arable land . IBM is combining power weather data – including historical, current and forecast data and weather prediction models from The Weather Company – with crop models to help improve yield forecast accuracy, generate value, and increase both farm production and profitability.
Roric Paulman, owner/operator of Paulman Farms in Southwest Nebraska, said: “As a farmer, the wild card is always weather. IBM overlays weather details with my own data and historical information to help me apply, verify, and make decisions. For example, our farm is in a highly restricted water basin, so the ability to better anticipate rain not only saves me money but also helps me save precious natural resources.”
New crop models include corn, wheat, soy, cotton, sorghum, barley, sugar cane and potato, with more coming soon. These models will now be available in the Africa, U.S. Canada, Mexico, and Brazil, as well as new markets across Europe and Australia.
Kristen Lauria, general manager of Watson Media and Weather Solutions at IBM, said: “These days farmers don’t just farm food, they also cultivate data – from drones flying over fields to smart irrigation systems, and IoT sensors affixed to combines, seeders, sprayers and other equipment. Most of the time, this data is left on the vine — never analysed or used to derive insights. Watson Decision Platform for Agriculture aims to change that by offering tools and solutions to help growers make more informed decisions about their crops.”
The average farm generates an estimated 500,000 data points per day, which will grow to 4 million data points by 2036 . Applying AI and analysis to aggregated field, machine and environmental data can help improve shared insights between growers and enterprises across the agriculture ecosystem. With a better view of the fields, growers can see what’s working on certain farms and share best practices with other farmers. The platform assesses data in an electronic field record to identify and communicate crop management patterns and insights. Enterprise businesses such as food companies, grain processors, or produce distributors can then work with farmers to leverage those insights. It helps track crop yield as well as the environmental, weather and plant biologic conditions that go into a good or bad yield, such as irrigation management, pest and disease risk analysis and cohort analysis for comparing similar subsets of fields.
The result isn’t just more productive farmers. Watson Decision Platform for Agriculture could help a livestock company eliminate a certain mold or fungus from feed supply grains or help identify the best crop irrigation practices for farmers to use in drought-stricken areas like California. It could help deliver the perfect French fry for a fast food chain that needs longer – not fatter – potatoes from its network of growers. Or it could help a beer distributor produce a more affordable premium beer by growing higher quality barley that meets the standard required to become malting barley.
Watson Decision Platform for Agriculture is built on IBM PAIRS Geoscope from IBM Research, which quickly processes massive, complex geospatial and time-based datasets collected by satellites, drones, aerial flights, millions of IoT sensors and weather models. It crunches large, complex data and creates insights quickly and easily so farmers and food companies can focus on growing crops for global communities.
IBM and The Weather Company help the agriculture industry find value in weather insights. IBM Research collaborates with start up Hello Tractor to integrate The Weather Company data, remote sensing data (e.g., satellite), and IoT data from tractors. IBM also works with crop nutrition leader Yara to include hyperlocal weather forecasts in its digital platform for real-time recommendations, tailored to specific fields or crops. IBM acquired The Weather Company in 2016 and has since been helping clients better understand and mitigate the cost of weather on their businesses. The global expansion of Watson Decision Platform for Agriculture is the latest innovation in IBM’s efforts to make weather a more predictable business consideration. Also just announced, Weather Signals is a new AI-based tool that merges The Weather Company data with a company’s own operations data to reveal how minor fluctuations in weather affects business.
The combination of rich weather forecast data from The Weather Company and IBM’s AI and Cloud technologies is designed to provide a unique capability, which is being leveraged by agriculture, energy and utility companies, airlines, retailers and many others to make informed business decisions.
 The UN Department of Economic and Social Affairs, “World Population Prospects: The 2017 Revision”
 Business Insider Intelligence, 2016 report: https://www.businessinsider.com/internet-of-things-smart-agriculture-2016-10
What if Amazon used AI to take on factories?
By ANTONY BOURNE, IFS Global Industry Director for Manufacturing
Amazon recently announced record profits of $3.03bn, breaking its own record for the third consecutive time. However, Amazon appears to be at a crossroads as to where it heads next. Beyond pouring additional energy into Amazon Prime, many have wondered whether the company may decide to enter an entirely new sector such as manufacturing to drive future growth, after all, it seems a logical step for the company with its finger in so many pies.
At this point, it is unclear whether Amazon would truly ‘get its hands dirty’ by manufacturing its own products on a grand scale. But what if it did? It’s worth exploring this reality. What if Amazon did decide to move into manufacturing, a sector dominated by traditional firms and one that is yet to see an explosive tech rival enter? After all, many similarly positioned tech giants have stuck to providing data analytics services or consulting to these firms rather than genuinely engaging with and analysing manufacturing techniques directly.
If Amazon did factories
If Amazon decided to take a step into manufacturing, it is likely that they could use the Echo range as a template of what AI can achieve. In recent years,Amazon gained expertise on the way to designing its Echo home speaker range that features Alexa, an artificial intelligence and IoT-based digital assistant.Amazon could replicate a similar form with the deployment of AI and Industrial IoT (IIoT) to create an autonomously-run smart manufacturing plant. Such a plant could feature IIoT sensors to enable the machinery to be run remotely and self-aware; managing external inputs and outputs such as supply deliveries and the shipping of finished goods. Just-in-time logistics would remove the need for warehousing while other machines could be placed in charge of maintenance using AI and remote access. Through this, Amazon could radically reduce the need for human labour and interaction in manufacturing as the use of AI, IIoT and data analytics will leave only the human role for monitoring and strategic evaluation. Amazon has been using autonomous robots in their logistics and distribution centres since 2017. As demonstrated with the Echo range, this technology is available now, with the full capabilities of Blockchain and 5G soon to be realised and allowing an exponentially-increased amount of data to be received, processed and communicated.
Manufacturing with knowledge
Theorising what Amazon’s manufacturing debut would look like provides a stark learning opportunity for traditional manufacturers. After all, wheneverAmazon has entered the fray in other traditional industries such as retail and logistics, the sector has never remained the same again. The key takeaway for manufacturers is that now is the time to start leveraging the sort of technologies and approaches to data management that Amazon is already doing in its current operations. When thinking about how to implement AI and new technologies in existing environments, specific end-business goals and targets must be considered, or else the end result will fail to live up to the most optimistic of expectations. As with any target and goal, the more targeted your objectives, the more competitive and transformative your results. Once specific targets and deliverables have been considered, the resources and methods of implementation must also be considered. As Amazon did with early automation of their distribution and logistics centres, manufacturers need to implement change gradually and be focused on achieving small and incremental results that will generate wider momentum and the appetite to lead more expansive changes.
In implementing newer technologies, manufacturers need to bear in mind two fundamental aspects of implementation: software and hardware solutions. Enterprise Resource Planning (ERP) software, which is increasingly bolstered by AI, will enable manufacturers to leverage the data from connected IoT devices, sensors, and automated systems from the factory floor and the wider business. ERP software will be the key to making strategic decisions and executing routine operational tasks more efficiently. This will allow manufacturers to keep on top of trends and deliver real-time forecasting and spot any potential problems before they impact the wider business.
As for the hardware, stock management drones and sensor-embedded hardware will be the eyes through which manufacturers view the impact emerging technologies bring to their operations. Unlike manual stock audits and counting, drones with AI capabilities can monitor stock intelligently around production so that operations are not disrupted or halted. Manufacturers will be able to see what is working, what is going wrong, and where there is potential for further improvement and change.
Knowledge for manufacturing
For many traditional manufacturers, they may see Amazon as a looming threat, and smart-factory technologies such as AI and Robotic Process Automation (RPA) as a far off utopia. However, 2019 presents a perfect opportunity for manufacturers themselves to really determine how the tech giants and emerging technologies will affect the industry. Technologies such as AI and IoT are available today; and the full benefits of these technologies will only deepen as they are implemented alongside the maturing of other emerging technologies such as 5G and Blockchain in the next 3-5 years. Manufacturers need to analyse the needs which these technologies can address and produce a proper plan on how to gradually implement these technologies to address specific targets and deliverables. AI-based software and hardware solutions will fundamentally revolutionise manufacturing, yet for 2019, manufacturers just have to be willing to make the first steps in modernisation.