Podcasts about as we may think

Play Episode Listen Later Apr 18, 2022 56:25

We travel back in time to before our heroes Sol, Titan, White Knight, and Muse were even born, to a time when Halcyon City shone bright, and beamed with hope and promise. Join us as we turn back the pages for our hero's mentor Burnout when the Flame of Freedom was just a spark in this week's epic conclusion of MASKS: The Spark of Freedom Part Two presented by Delinquent Comics. This episode of Delinquent Comics starredJustin Allen as BurnoutShawn Delp as GehennaAnd Ben Wallis as Halcyon City.Anyone Can Wear the Mask is a tabletop role playing and world building game written and created by Jeff Stormer and can be found for purchase on itch.io.This episode featured the songs: Tension is Rising, Right, A Difficult Subject, and Intelligent Galaxy all by The Insider and can be found on the album: Alls Fair in Love of Wax. It also featured Iron Anura, Nassaruhk & Pairuhk, Marsh, Hylidae and Torpor all by R.E.W. and can be found on the album: Anura.It also featured the songs dark, and park both by Horiso and can be found on the album Isha Ashi. It also featured the songs: As We May Think, Time Flux, Headphonetic, and Factum par Fictio all by Revolution Void and can be found on the albums: Increase the Dosage, Thread Soul, and The Politics of Desire.This episode was edited and produced by Justin Allen, Ben Wallis, and Shawn Delp.

The Spark of Freedom Issue 2 of 2

Play Episode Listen Later Apr 18, 2022 56:25

We travel back in time to before our heroes Sol, Titan, White Knight, and Muse were even born, to a time when Halcyon City shone bright, and beamed with hope and promise. Join us as we turn back the pages for our hero's mentor Burnout when the Flame of Freedom was just a spark in this week's epic conclusion of MASKS: The Spark of Freedom Part Two presented by Delinquent Comics. This episode of Delinquent Comics starredJustin Allen as BurnoutShawn Delp as GehennaAnd Ben Wallis as Halcyon City.Anyone Can Wear the Mask is a tabletop role playing and world building game written and created by Jeff Stormer and can be found for purchase on itch.io.This episode featured the songs: Tension is Rising, Right, A Difficult Subject, and Intelligent Galaxy all by The Insider and can be found on the album: Alls Fair in Love of Wax. It also featured Iron Anura, Nassaruhk & Pairuhk, Marsh, Hylidae and Torpor all by R.E.W. and can be found on the album: Anura.It also featured the songs dark, and park both by Horiso and can be found on the album Isha Ashi. It also featured the songs: As We May Think, Time Flux, Headphonetic, and Factum par Fictio all by Revolution Void and can be found on the albums: Increase the Dosage, Thread Soul, and The Politics of Desire.This episode was edited and produced by Justin Allen, Ben Wallis, and Shawn Delp.

Bill Atkinson's HyperCard

Play Episode Listen Later Jan 29, 2022 14:22

We had this Mac lab in school. And even though they were a few years old at the time, we had a whole room full of Macintosh SEs. I'd been using the Apple II Cs before that and these just felt like Isaac Asimov himself dropped them off just for me to play with. Only thing: no BASIC interpreter. But in the Apple menu, tucked away in the corner was a little application called HyperCard. HyperCard wasn't left by Asimov, but instead burst from the mind of Bill Atkinson. Atkinson was the 51st employee at Apple and a former student of Jeff Raskin, the initial inventor of the Mac before Steve Jobs took over. Steve Jobs convinced him to join Apple where he started with the Lisa and then joined the Mac team until he left with the team who created General Magic and helped bring shape to the world of mobile devices. But while at Apple he was on the original Mac team developing the menu bar, the double-click, Atkinson dithering, MacPaint, QuickDraw, and HyperCard. Those were all amazing tools and many came out of his work on the original 1984 Mac and the Lisa days before that. But HyperCard was something entirely different. It was a glimpse into the future, even if self-contained on a given computer. See, there had been this idea floating around for awhile. Vannevar Bush initially introduced the world to a device with all the world's information available in his article “As We May Think” in 1946. Doug Engelbart had a team of researchers working on the oN-Line System that saw him give “The Mother of All Demos in 1968” where he showed how that might look, complete with a graphical interface and hypertext, including linked content. Ted Nelson introduced furthered the ideas in 1969 of having linked content, which evolved into what we now call hyperlinks. Although Nelson thought ahead to include the idea of what he called transclusions, or the snippets of text displayed on the screen from their live, original source. HyperCard built on that wealth of information with a database that had a graphical front-end that allowed inserting media and a programming language they called HyperTalk. Databases were nothing new. But a simple form creator that supported graphics and again stressed simple, was new. Something else that was brewing was this idea of software economics. Brooks' Law laid it out but Barry Boehm's book on Software Engineering Economics took the idea of rapid application development another step forward in 1981. People wanted to build smaller programs faster. And so many people wanted to build tools that we needed to make it easier to do so in order for computers to make us more productive. Against that backdrop, Atkinson took some acid and came up with the idea for a tool he initially called WildCard. Dan Winkler signed onto the project to help build the programming language, HyperTalk, and they got to work in 1986. They changed the name of the program to HyperCard and released it in 1987 at MacWorld. Regular old people could create programs without knowing how to write code. There were a number of User Interface (UI) components that could easily be dropped on the screen, and true to his experience there was panel of elements like boxes, erasers, and text, just like we'd seen in MacPaint. Suppose you wanted a button, just pick it up from the menu and drop it where it goes. Then make a little script using the HyperText that read more like the English language than a programming language like LISP. Each stack might be synonymous with a web page today. And a card was a building block of those stacks. Consider the desktop metaphor extended to a rolodex of cards. Those cards can be stacked up. There were template cards and if the background on a template changed, that flowed to each card that used the template, like styles in Keynote might today. The cards could have text fields, video, images, buttons, or anything else an author could think of. And the author word is important. Apple wanted everyone to feel like they could author a hypercard stack or program or application or… app. Just as they do with Swift Playgrounds today. That never left the DNA. We can see that ease of use in how scripting is done in HyperTalk. Not only the word scripting rather than programming, but how HyperTalk is weakly typed. This is to say there's no memory safety or type safety, so a variable might be used as an integer or boolean. That either involves more work by the interpreter or compiler - or programs tend to crash a lot. Put the work on the programmers who build programming tools rather than the authors of HyperCard stacks. The ease of use and visual design made Hypercard popular instantly. It was the first of its kind. It didn't compile at first, although larger stacks got slow because HyperTalk was interpreted, so the team added a just-in-time compiler in 1989 with HyperCard 2.0. They also added a debugger. There were some funny behaviors. Like some cards could have objects that other cards in a stack didn't have. This led to many a migration woe for larger stacks that moved into modern tools. One that could almost be considered HyperCard 3, was FileMaker. Apple spun their software business out as Claris, who bought Noshuba software, which had this interesting little database program called Nutshell. That became FileMaker in 1985. By the time HyperCard was ready to become 3.0, FileMaker Pro was launched in 1990. Attempts to make Hypercard 3.0 were still made, but Hypercard had its run by the mid-1990s and died a nice quiet death. The web was here and starting to spread. The concept of a bunch of stacks on just one computer had run its course. Now we wanted pages that anyone could access. HyperCard could have become that but that isn't its place in history. It was a stepping stone and yet a milestone and a legacy that lives on. Because it was a small tool in a large company. Atkinson and some of the other team that built the original Mac were off to General Magic. Yet there was still this idea, this legacy. Hypercard's interface inspired many modern applications we use to create applications. The first was probably Delphi, from Borland. But over time Visual Studio (which we still use today) for Microsoft's Visual Basic. Even Powerpoint has some similarities with HyperCard's interface. WinPlus was similar to Hypercard as well. Even today, several applications and tools use HyperCard's ideas such as HyperNext, HyperStudio, SuperCard, and LiveCode. HyperCard also certainly inspired FileMaker and every Apple development environment since - and through that, most every tool we use to build software, which we call the IDE, or Integrated Development Environment. The most important IDE for any Apple developer is Xcode. Open Xcode to build an app and look at Interface Builder and you can almost feel Bill Atkinson's pupils dilated pupils looking back at you, 10 hours into a trip. And within those pupils visions - visions of graphical elements being dropped into a card and people digitized CD collections, built a repository for their book collection, put all the Grateful Dead shows they'd recorded into a stack, or even built an application to automate their business. Oh and let's not forget the Zine, or music and scene magazines that were so popular in the era that saw photocopying come down in price. HyperCard made for a pretty sweet Zine. HyperCard sprang from a trip when the graphical interface was still just coming into its own. Digital computing might have been 40 years old but the information theorists and engineers hadn't been as interested in making things easy to use. They wouldn't have been against it, but they weren't trying to appeal to regular humans. Apple was, and still is. The success of HyperCard seems to have taken everyone by surprise. Apple sold the last copy in 2004, but the legacy lives on. Successful products help to mass- Its success made a huge impact at that time as well on the upcoming technology. Its popularity declined in the mid-1990s and it died quietly when Apple sold its last copy in 2004. But it surely left a legacy that has inspired many - especially old-school Apple programmers, in today's “there's an app for that” world.

english apple mother law digital dna microsoft mac cd basic regular steve jobs wild card keynote databases grateful dead atkinson delphi nutshell ide isaac asimov zine asimov visual studio macworld xcode lisp supercard borland quick draw visual basic mac apps swift playgrounds claris hypercard general magic hypertext filemaker bill atkinson dan winkler ted nelson filemaker pro user interface ui all demos doug engelbart interface builder macpaint hypertalk as we may think hyperstudio

Of Heath Robinson Contraptions And The Colossus

Play Episode Listen Later Dec 14, 2021 19:46

The Industrial Revolution gave us the rise of factories all over the world in the 1800s. Life was moving faster and we were engineering complex solutions to mass produce items. And many expanded from there to engineer complex solutions for simple problems. Cartoonist Heath Robinson harnessed the reaction from normal humans to this changing world in the forms of cartoons and illustrations of elaborate machines meant to accomplish simple tasks. These became known as “Heath Robinson contraptions” and were a reaction to the changing and increasingly complicated world order as much as anything. Just think of the rapidly evolving financial markets as one sign of the times! Following World War I, other cartoonists made similar cartoons. Like Rube Goldberg, giving us the concept of Rube Goldberg machines in the US. And the very idea of breaking down simple operations into Boolean logic from those who didn't understand the “why” would have seemed preposterous. I mean a wheel with 60 teeth or a complex series of switches and relays to achieve the same result? And yet with flip-flop circuits one would be able to process infinitely faster than it would take that wheel to turn with any semblance of precision. The Industrial Revolution of our data was to come. And yet we were coming to a place in the world where we were just waking up to the reality of moving from analog to digital as Robinson passed away in 1944 with a series of electromechanical computers named after Robinson and then The Colossus. These came just one year after Claude Shannon and Alan Turing, two giants in the early history of computers, met at Bell Labs. And a huge step in that transition was a paper by Alan Turing in 1936 called "On Computable Numbers with an Application to the Entscheidungsproblem.” This would become the basis for a programmable computing machine concept and so before the war, Alan Turing had published papers about the computability of problems using what we now call a Turing machine - or recipes. Some of the work on that paper was inspired by Max Newman, who helped Turing go off to Princeton to work on all the maths, where Turing would get a PhD in 1938. He returned home and started working part-time at the Government Code and Cypher school during the pre-war buildup. Hitler invaded Poland the next year, sparking World War II. The Poles had gotten pretty good with codebreaking, being situated right between world powers Germany and Russia and their ability to see troop movements through decrypted communications was one way they were able to keep forces in optimal locations. And yet the Germans got in there. The Germans had built a machine called the Enigma that also allowed their Navy to encrypt communications. Unable to track their movements, Allied forces were playing a cat and mouse game and not doing very well at it. Turing came up with a new way of decrypting the messages and that went into a new version of the Polish Bomba. Later that year, the UK declared war on Germany. Turing's work resulted in a lot of other advances in cryptanalysis throughout the war. But he also brought home the idea of an electromechanical machine to break those codes - almost as though he'd written a paper on building machines to do such things years before. The Germans had given away a key to decrypt communications accidentally in 1941 and the codebreakers at Bletchley Park got to work on breaking the machines that used the Lorenz Cipher in new and interesting ways. The work had reduced the amount of losses - but they needed more people. It was time intensive to go through the possible wheel positions or guess at them, and every week meant lives lost. Or they needed more automation of people tasks… So they looked to automate the process. Turing and the others wrote to Churchill directly. Churchill started his memo to General Ismay with “ACTION THIS DAY” and so they were able to get more bombes up and running. Bill Tutte and the codebreakers worked out the logic to process the work done by hand. The same number of codebreakers were able to a ton more work. The first pass was a device with uniselectors and relays. Frank Morrell did the engineering design to process the logic. And so we got the alpha test of an automation machine they called the Tunny. The start positions were plugged in by hand and it could still take weeks to decipher messages. Max Newman, Turing's former advisor and mentor, got tapped to work on the project and Turing was able to take the work of Polish code breakers and others and add sequential conditional probability to guess at the settings of the 12 wheels of an Enigma machine and thus get to the point they could decipher messages coming out of the German navy on paper. No written records indicate that Turing was involved much in the project beyond that. Max Newman developed the specs, heavily influenced by Turing's previous work. They got to work on an electro-mechanical device we now call the Heath Robinson. They needed to be able to store data. They used paper tape - which could process a thousand characters per second using photocell readers - but there were two and they had to run concurrently. Tape would rip and two tapes running concurrently meant a lot might rip. Charles Wynn-Williams was a brilliant physicist who worked with electric waves since the late 1920s at Trinity College, Cambridge and was recruited from a project helping to develop RADAR because he'd specifically worked on electronic counters at Cambridge. That work went into the counting unit, counting how many times a function returned a true result. As we saw with Bell Labs, the telephone engineers were looking for ways to leverage switching electronics to automate processes for the telephone exchange. Turing recommended they bring in telephone engineer Tommy Flowers to design the Combining unit, which used vacuum tubes to implement Boolean logic - much as the paper Shannon wrote in 1936 that he gave Turing over tea at Bell labs earlier 1943. It's likely Turing would have also heard of the calculator George Stibitz of Bell Labs built out of relay switches all the way back in 1937. Slow but more reliable than the vacuum tubes of the era. And it's likely he influenced those he came to help by collaborating on encrypted voice traffic and likely other projects as much if not more. Inspiration is often best found at the intersectionality between ideas and cultures. Flowers looked to use vacuum tubes where the wheel patterns were produced. This gave one less set of paper tapes and infinitely more reliability. And a faster result. The programs were stored but they were programmable. Input was made using the shift registers from the paper tape and thyratron rings that simulated the bitstream for the wheels. There was a master control unit that handled the timing between the clock, signals, readouts, and printing. It didn't predate the Von Neumann architecture. But it didn't not. The switch panel had a group of switches used to define the algorithm being used with a plug-board defining conditions. The combination provided billions of combinations for logic processing. Vacuum tube valves were still unstable but they rarely blew when on, it was the switching process. So if they could have the logic gates flow through a known set of wheel settings the new computer would be more stable. Just one thing - they needed 1,500 valves! This thing would be huge! And so the Colossus Mark 1 was approved by W.G. Radley in 1943. It took 50 people 11 months to build and was able to compute wheel settings for ciphered message tapes. Computers automating productivity at its finest. The switches and plugs could be repositioned and so not only was Colossus able get messages decrypted in hours but could be reprogrammed to do other tasks. Others joined and they got the character reading up to almost 10,000 characters a second. They improved on the design yet again by adding shift registers and got over four times the speeds. It could now process 25,000 characters per second. One of the best uses was to confirm that Hitler got tricked into thinking the attack at Normandy at D-Day would happen elsewhere. And so the invasion of Normandy was safe to proceed. But the ability to reprogram made it a mostly universal computing machine - proving the Turing machine concept and fulfilling the dreams of Charles Babbage a hundred years earlier. And so the war ended in 1945. After the war, The Colossus machines were destroyed - except the two sent to British GHCQ where they ran until 1960. So the simple story of Colossus is that it was a series of computers built in England from 1943 to 1945, at the heart of World War II. The purpose: cryptanalysis - or code breaking. Turing went on to work on the Automatic Computing Engine at the National Physical Laboratory after the war and wrote a paper on the ACE - but while they were off to a quick start in computing in England having the humans who knew the things, they were slow to document given that their wartime work was classified. ENIAC came along in 1946 as did the development of Cybernetics by Norbert Wiener. That same year Max Newman wrote to John Von Neumann (Wiener's friend) about building a computer in England. He founded the Royal Society Computing Machine Laboratory at Victory University of Manchester, got Turing out to help and built the Manchester Baby, along with Frederic Williams and Thomas Kilburn. In 1946 Newman would also decline becoming Sir Newman when he rejected becoming an OBE, or Officer of the Order of the British Empire, over the treatment of his protege Turing not being offered the same. That's leadership. They'd go on to collaborate on the Manchester Mark I and Ferranti Mark I. Turing would work on furthering computing until his death in 1954, from taking cyanide after going through years of forced estrogen treatments for being a homosexual. He has since been pardoned post Following the war, Flowers tried to get a loan to start a computer company - but the very idea was ludicrous and he was denied. He retired from the Post Office Research Station after spearheading the move of the phone exchange to an electric, or what we might think of as a computerized exchange. Over the next decade, the work from Claude Shannon and other mathematicians would perfect the implementation of Boolean logic in computers. Von Neumann only ever mentioned Shannon and Turing in his seminal 1958 paper called The Computer And The Brain. While classified by the British government the work on Colossus was likely known to Von Neumann, who will get his own episode soon - but suffice it to say was a physicist turned computer scientist and worked on ENIAC to help study and develop atom bombs - and who codified the von Neumann architecture. We did a whole episode on Turing and another on Shannon, and we have mentioned the 1945 article As We May Think where Vannevar Bush predicted and inspired the next couple generations of computer scientists following the advancements in computing around the world during the war. He too would have likely known of the work on Colossus at Bletchley Park. Maybe not the specifics but he certainly knew of ENIAC - which unlike Colossus was run through a serious public relations machine. There are a lot of heroes to this story. The brave men and women who worked tirelessly to break, decipher, and analyze the cryptography. The engineers who pulled it off. The mathematicians who sparked the idea. The arrival of the computer was almost deterministic. We had work on the Atanasoff-Berry Computer at Iowa State, work at Bell Labs, Norbert Wiener's work on anti-aircraft guns at MIT during the war, Konrad Zuse's Z3, Colossus, and other mechanical and electromechanical devices leading up to it. But deterministic doesn't mean lacking inspiration. And what is the source of inspiration and when mixed with perspiration - innovation? There were brilliant minds in mathematics, like Turing. Brilliant physicists like Wynn-Williams. Great engineers like Flowers. That intersection between disciplines is the wellspring of many an innovation. Equally as important, then there's a leader who can take the ideas, find people who align with a mission, and help clear roadblocks. People like Newman. When they have domain expertise and knowledge - and are able to recruit and keep their teams inspired, they can change the world. And then there are people with purse strings who see the brilliance and can see a few moves ahead on the chessboard - like Churchill. They make things happen. And finally, there are the legions who carried on the work in theoretical, practical, and in the pure sciences. People who continue the collaboration between disciplines, iterate, and bring products to ever growing markets. People who continue to fund those innovations. It can be argued that our intrepid heroes in this story helped win a war - but that the generations who followed, by connecting humanity and bringing productivity gains to help free our minds to solve bigger and bigger problems will hopefully some day end war. Thank you for tuning in to this episode of the History of Computing Podcast. We hope to cover your contributions. Drop us a line and let us know how we can. And thank you so much for listening. We are so, so lucky to have you.

history uk england british germany phd russia inspiration german mit drop world war ii navy computers adolf hitler manchester poland robinson cambridge flowers application officer polish brilliant tape newman radar d day input churchill unable enigma equally normandy british empire iowa state industrial revolution allied colossus vacuum poles obe neumann trinity college turing alan turing cypher cryptography cybernetics rube goldberg bell labs bletchley park radley boolean charles babbage eniac claude shannon von neumann z3 norbert wiener konrad zuse tunny national physical laboratory government code max newman tommy flowers as we may think bill tutte

Vega Rising Issue 6

Play Episode Listen Later Nov 22, 2021 48:40

Content Warning: This show contains strong themes of memory manipulation, memory theft, and memory loss. How will our heroes squeeze the secrets out of the galaxy this week on MASKS: Vega Rising: Issue 6: The Villainous Vixens Revealed presented by Delinquent Comics. This episode of Delinquent Comics starredAshton Lorelle as SolJustin Allen as TitanConnor Casteel as White KnightShawn Delp as MuseAnd Ben Wallis as the Game Master.Masks: A New Generation is the award-winning tabletop roleplaying game by Brendan Conway and published by Magpie Games.This episode featured the songs: Tension is Rising and Intelligent Galaxy both by The Insider and can be found on the album: Alls Fair in Love of Wax. It also featured Mt. Etna by R.E.W. and can be found on the album: Tephra.It also featured the songs: Habitual Ritual, Time Flux, The Narrative Changes, and As We May Think all by Revolution Void and can be found on the albums: Increase the Dosage, Thread Soul, and The Politics of Desire.This episode was edited and produced by Ben Wallis and Shawn Delp.

Vega Rising Issue 6

Play Episode Listen Later Nov 22, 2021 48:40

Content Warning: This show contains strong themes of memory manipulation, memory theft, and memory loss. How will our heroes squeeze the secrets out of the galaxy this week on MASKS: Vega Rising: Issue 6: The Villainous Vixens Revealed presented by Delinquent Comics. This episode of Delinquent Comics starredAshton Lorelle as SolJustin Allen as TitanConnor Casteel as White KnightShawn Delp as MuseAnd Ben Wallis as the Game Master.Masks: A New Generation is the award-winning tabletop roleplaying game by Brendan Conway and published by Magpie Games.This episode featured the songs: Tension is Rising and Intelligent Galaxy both by The Insider and can be found on the album: Alls Fair in Love of Wax. It also featured Mt. Etna by R.E.W. and can be found on the album: Tephra.It also featured the songs: Habitual Ritual, Time Flux, The Narrative Changes, and As We May Think all by Revolution Void and can be found on the albums: Increase the Dosage, Thread Soul, and The Politics of Desire.This episode was edited and produced by Ben Wallis and Shawn Delp.

Do You Yahoo!?

Play Episode Listen Later Aug 20, 2021 28:15

The simple story of Yahoo! Is that they were an Internet search company that came out of Stanford during the early days of the web. They weren't the first nor the last. But they represent a defining moment in the rise of the web as we know it today, when there was enough content out there that there needed to be an easily searchable catalog of content. And that's what Stanford PhD students David Philo and Jerry Yang built. As with many of those early companies it began as a side project called “Jerry and David's Guide to the World Wide Web.” And grew into a company that at one time rivaled any in the world. At the time there were other search engines and they all started adding portal aspects to the site growing fast until the dot-com bubble burst. They slowly faded until being merged with another 90s giant, AOL, in 2017 to form Oath, which got renamed to Verizon Media in 2019 and then effectively sold to investment management firm Apollo Global Management in 2021. Those early years were wild. Yang moved to San Jose in the 70s from Taiwan, and earned a bachelors then a masters at Stanford - where he met David Filo in 1989. Filo is a Wisconsin kid who moved to Stanford and got his masters in 1990. The two went to Japan in 1992 on an exchange program and came home to work on their PhDs. That's when they started surfing the web. Within two years they started their Internet directory in 1994. As it grew they hosted the database on Yang's student computer called akebono and the search engine on konishiki, which was Filo's. They renamed it to Yahoo, short for Yet Another Hierarchical Officious Oracle - after all they maybe considered themselves Yahoos at the time. And so Yahoo began life as akebono.stanford.edu/~yahoo. Word spread fast and they'd already had a million hits by the end of 1994. It was time to move out of Stanford. Mark Andreesen offered to let them move into Netscape. They bought a domain in 1995 and incorporated the company, getting funding from Sequoia Capital raising $3,000,000. They tinkered with selling ads on the site to fund buying more servers but there was a lot of businessing. They decided that they would bring in Tim Koogle (which ironically rhymes with Google) to be CEO who brought in Jeff Mallett from Novell's consumer division to be the COO. They were the suits and got revenues up to a million dollars. The idea of the college kids striking gold fueled the rise of other companies and Yang and Filo became poster children. Applications from all over the world for others looking to make their mark started streaming in to Stanford - a trend that continues today. Yet another generation was about to flow into Silicon Valley. First the chip makers, then the PC hobbyists turned businesses, and now the web revolution. But at the core of the business were Koogle and Mallett, bringing in advertisers and investors. And the next year needing more and more servers and employees to fuel further expansion, they went public, selling over two and a half million shares at $13 to raise nearly $34 million. That's just one year after a gangbuster IPO from Netscape. The Internet was here. Revenues shot up to $20 million. A concept we repeatedly look at is the technological determinism that industries go through. At this point it's easy to look in the rear view mirror and see change coming at us. First we document information - like Jerry and David building a directory. Then we move it to a database so we can connect that data. Thus a search engine. Given that Yahoo! was a search engine they were already on the Internet. But the next step in the deterministic application of modern technology is to replace human effort with increasingly sophisticated automation. You know, like applying basic natural language processing, classification, and polarity scoring algorithms to enrich the human experience. Yahoo! hired “surfers” to do these tasks. They curated the web. Yes, they added feeds for news, sports, finance, and created content. Their primary business model was to sell banner ads. And they pioneered the field. Banner ads mean people need to be on the site to see them. So adding weather, maps, shopping, classifieds, personal ads, and even celebrity chats were natural adjacencies given that mental model. Search itself was almost a competitor, sending people to other parts of the web that they weren't making money off eyeballs. And they were pushing traffic to over 65 million pages worth of data a day. They weren't the only ones. This was the portal era of search and companies like Lycos, Excite, and InfoSeek were following the same model. They created local directories and people and companies could customize the look and feel. Their first designer, David Shen, takes us through the user experience journey in his book Takeover! The Inside Story the Yahoo Ad Revolution. They didn't invent pay-per-clic advertising but did help to make it common practice and proved that money could be made on this whole new weird Internet thing everyone was talking about. The first ad they sold was for MCI and from there they were practically printing money. Every company wanted in on the action - and sales just kept going up. Bill Clinton gave them a spot in the Internet Village during his 1997 inauguration and they were for a time seemingly synonymous with the Internet. The Internet was growing fast. Cataloging the Internet and creating content for the Internet became a larger and larger manual task. As did selling ads, which was a manual transaction requiring a larger and larger sales force. As with other rising internet properties, people dressed how they wanted, they'd stay up late building code or content and crash at the desk. They ran funny cheeky ads with that yodel - becoming a brand that people knew and many equated to the Internet. We can thank San Francisco's Black Rocket ad agency for that. They grew fast. The founders made several strategic acquisitions and gobbled up nearly every category of the Internet that has each grown to billions of dollars. They bought Four 11 for $95 million in their first probably best acquisition, and used them to create Yahoo! Mail in 1997 and a calendar in 1998. They had over 12 million Yahoo! Email users by he end of the year, inching their way to the same number of AOL users out there. There were other tools like Yahoo Briefcase, to upload files to the web. Now common with cloud storage providers like Dropbox, Box, Google Drive, and even Office 365. And contacts and Messenger - a service that would run until 2018. Think of all the messaging apps that have come with their own spin on the service since. 1998 also saw the acquisition of Viaweb, founded by the team that would later create Y Combinator. It was just shy of a $50M acquisition that brought the Yahoo! Store - which was similar to the Shopify of today. They got a $250 million investment from Softbank, bought Yoyodyne, and launched AT&T's WorldNet service to move towards AOL's dialup services. By the end of the year they were closing in on 100 million page views a day. That's a lot of banners shown to visitors. But Microsoft was out there, with their MSN portal at the height of the browser wars. Yahoo! bought Broadcast.com in 1999 saddling the world with Mark Cuban. They dropped $5.7 billion for 300 employees and little more than an ISDN line. Here, they paid over a 100x multiple of annual revenues and failed to transition sellers into their culture. Sales cures all. In his book We Were Yahoo! Jeremy Ring describes the lays much of the blame of the failure to capitalize on the acquisition as not understanding the different selling motion. I don't remember him outright saying it was hubris, but he certainly indicates that it should have worked out and that broadcast.com was could have been what YouTube would become. Another market lost in a failed attempt at Yahoo TV. And yet many of these were trends started by AOL. They also bought GeoCities in 99 for $3.7 billion. Others have tried to allow for fast and easy site development - the no code wysiwyg web. GeoCities lasted until 2009 - a year after Google launched Google Sites. And we have Wix, Squarespace, WordPress, and so many others offering similar services today. As they grew some of the other 130+ search engines at the time folded. The new products continued. The Yahoo Notebook came before Evernote. Imagine your notes accessible to any device you could log into. The more banners shown, the more clicks. Advertisers could experiment in ways they'd never been able to before. They also inked distribution deals, pushing traffic to other site that did things they didn't. The growth of the Internet had been fast, with nearly 100 million people armed with Internet access - and yet it was thought to triple in just the next three years. And even still many felt a bubble was forming. Some, like Google, had conserved cash - others like Yahoo! Had spent big on acquisitions they couldn't monetize into truly adjacent cash flow generating opportunities. And meanwhile they were alienating web properties by leaning into every space that kept eyeballs on the site. By 2000 their stock traded at $118.75 and they were the most valuable internet company at $125 billion. Then as customers folded when the dot-com bubble burst, the stock fell to $8.11 the next year. One concept we talk about in this podcast is a lost decade. Arguably they'd entered into theirs around the time the dot-com bubble burst. They decided to lean into being a media company even further. Again, showing banners to eyeballs was the central product they sold. They brought in Terry Semel in 2001 using over $100 million in stock options to entice him. And the culture problems came fast. Semel flew in a fancy jet, launched television shows on Yahoo! and alienated programmers, effectively creating an us vs them and de-valuing the work done on the portal and search. Work that could have made them competitive with Google Adwords that while only a year old was already starting to eat away at profits. But media. They bought a company called LaunchCast in 2001, charging a monthly fee to listen to music. Yahoo Music came before Spotify, Pandora, Apple Music, and even though it was the same year the iPod was released, they let us listen to up to 1,000 songs for free or pony up a few bucks a month to get rid of ads and allow for skips. A model that has been copied by many over the years. By then they knew that paid search was becoming a money-maker over at Google. Overture had actually been first to that market and so Yahoo! Bought them for $1.6 billion in 2003. But again, they didn't integrate the team and in a classic “not built here” moment started Project Panama where they'd spend three years building their own search advertising platform. By the time that shipped the search war was over and executives and great programmers were flowing into other companies all over the world. And by then they were all over the world. 2005 saw them invest $1 billion in a little company called Alibaba. An investment that would accelerate Alibaba to become the crown jewel in Yahoo's empire and as they dwindled away, a key aspect of what led to their final demise. They bought Flickr in 2005 for $25M. User generated content was a thing. And Flickr was almost what Instagram is today. Instead we'd have to wait until 2010 for Instagram because Flickr ended up yet another of the failed acquisitions. And here's something wild to thin about - Stewart Butterfield and Cal Henderson started another company after they sold Flickr. Slack sold to Salesforce for over $27 billion. Not only is that a great team who could have turned Flickr into something truly special, but if they'd been retained and allowed to flourish at Yahoo! they could have continued building cooler stuff. Yikes. Additionally, Flickr was planning a pivot into social networking, right before a time when Facebook would take over that market. If fact, they tried to buy Facebook for just over a billion dollars in 2006. But Zuckerberg walked away when the price went down after the stock fell. They almost bought YouTube and considered buying Apple, which is wild to think about today. Missed opportunities. And Semmel was the first of many CEOs who lacked vision and the capacity to listen to the technologists - in a technology company. These years saw Comcast bring us weather.com, the rise of espn online taking eyeballs away from Yahoo! Sports, Gmail and other mail services reducing reliance on Yahoo! Mail. Facebook, LinkedIn, and other web properties rose to take ad placements away. Even though Yahoo Finance is still a great portal even sites like Bloomberg took eyeballs away from them. And then there was the rise of user generated content - a blog for pretty much everything. Jerry Yang came back to run the show in 2007 then Carol Bartz from 2009 to 2011 then Scott Thompson in 2012. None managed to turn things around after so much lost inertia - and make no mistake, inertia is the one thing that can't be bought in this world. Wisconsin's Marissa Mayer joined Yahoo! In 2012. She was Google's 20th employee who'd risen through the ranks from writing code to leading teams to product manager to running web products and managing not only the layout of that famous homepage but also helped deliver Google AdWords and then maps. She had the pedigree and managerial experience - and had been involved in M&A. There was an immediate buzz that Yahoo! was back after years of steady decline due to incoherent strategies and mismanaged acquisitions. She pivoted the business more into mobile technology. She brought remote employees back into the office. She implemented a bell curve employee ranking system like Microsoft did during their lost decade. They bought Tumblr in 2013 for $1.1 billion. But key executives continued to leave - Tumbler's value dropped, and the stock continued to drop. Profits were up, revenues were down. Investing in the rapidly growing China market became all the rage. The Alibaba investment was now worth more than Yahoo! itself. Half the shares had been sold back to Alibaba in 2012 to fund Yahoo! pursuing the Mayer initiatives. And then there was Yahoo Japan, which continued to do well. After years of attempts, activist investors finally got Yahoo! to spin off their holdings. They moved most of the shares to a holding company which would end up getting sold back to Alibaba for tens of billions of dollars. More missed opportunities for Yahoo! And so in the end, they would get merged with AOL - the two combined companies worth nearly half a trillion dollars at one point to become Oath in 2017. Mayer stepped down and the two sold for less than $5 billion dollars. A roller coaster that went up really fast and down really slow. An empire that crumbled and fragmented. Arguably, the end began in 1998 when another couple of grad students at Stanford approached Yahoo to buy Google for $1M. Not only did Filo tell them to try it alone but he also introduced them to Michael Moritz of Sequoia - the same guy who'd initially funded Yahoo!. That wasn't where things really got screwed up though. It was early in a big change in how search would be monetized. But they got a second chance to buy Google in 2002. By then I'd switched to using Google and never looked back. But the CEO at the time, Terry Semel, was willing to put in $3B to buy Google - who decided to hold out for $5B. They are around a $1.8T company today. Again, the core product was selling advertising. And Microsoft tried to buy Yahoo! In 2008 for over 44 billion dollars to become Bing. Down from the $125 billion height of the market cap during the dot com bubble. And yet they eventually sold for less than four and a half billion in 2016 and went down in value from there. Growth stocks trade at high multiples but when revenues go down the crash is hard and fast. Yahoo! lost track of the core business - just as the model was changing. And yet never iterated it because it just made too much money. They were too big to pivot from banners when Google showed up with a smaller, more bite-sized advertising model that companies could grow into. Along the way, they tried to do too much. They invested over and over in acquisitions that didn't work because they ran off the innovative founders in an increasingly corporate company that was actually trying to pretend not to be. We have to own who we are and become. And we have to understand that we don't know anything about the customers of acquired companies and actually listen - and I mean really listen - when we're being told what those customers want. After all, that's why we paid for the company in the first place. We also have to avoid allowing the market to dictate a perceived growth mentality. Sure a growth stock needs to hit a certain number of revenue increase to stay considered a growth stock and thus enjoy the kind of multiples for market capitalization. But that can drive short term decisions that don't see us investing in areas that don't effectively manipulate stocks. Decisions like trying to keep eyeballs on pages with our own content rather than investing in the user generated content that drove the Web 2.0 revolution. The Internet can be a powerful medium to find information, allow humans to do more with less, and have more meaningful experiences in this life. But just as Yahoo! was engineering ways to keep eyeballs on their pages, the modern Web 2.0 era has engineered ways to keep eyeballs on our devices. And yet what people really want is those meaningful experiences, which happen more when we aren't staring at our screens than when we are. As I look around at all the alerts on my phone and watch, I can't help but wonder if another wave of technology is coming that disrupts that model. Some apps are engineered to help us lead healthier lifestyles and take a short digital detoxification break. Bush's Memex in “As We May Think” was arguably an Apple taken from the tree of knowledge. If we aren't careful, rather than the dream of computers helping humanity do more and free our minds to think more deeply we are simply left with less and less capacity to think and less and less meaning. The Memex came and Yahoo! helped connect us to any content we might want in the world. And yet, like so many others, they stalled in the phase they were at in that deterministic structure that technologies follow. Too slow to augment human labor with machine learning like Google did - but instead too quick to try and do everything for everyone with no real vision other than be everything to everyone. And so the cuts went on slowly for a long time, leaving employees constantly in fear of losing their jobs. As you listen to this if I were to leave a single parting thought - it would be that companies should always be willing to cannibalize their own businesses. And yet we have to have a vision that our teams rally behind for how that revenue gets replaced. We can't fracture a company and just sprawl to become everything for everyone but instead need to be targeted and more precise. And to continue to innovate each product beyond the basic machine learning and into deep learning and beyond. And when we see those who lack that focus, don't get annoyed but instead get stoked - that's called a disruptive opportunity. And if there's someone with 1,000 developers in a space, Nicholas Carlson in his book “Marissa Mayer and the Fight To Save Yahoo!” points out that one great developer is worth a thousand average ones. And even the best organizations can easily turn great developers into average ones for a variety of reason. Again, we can call these opportunities. Yahoo! helped legitimize the Internet. For that we owe them a huge thanks. And we can fast follow their adjacent expansions to find a slew of great and innovative ideas that increased the productivity of humankind. We owe them a huge thanks for that as well. Now what opportunities do we see out there to propel us further yet again?

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Babbage to Bush: An Unbroken Line Of Computing

Play Episode Listen Later Jul 29, 2021 14:28

The amount published in scientific journals has exploded over the past few hundred years. This helps in putting together a history of how various sciences evolved. And sometimes helps us revisit areas for improvement - or predict what's on the horizon. The rise of computers often begins with stories of Babbage. As we've covered a lot came before him and those of the era were often looking to automate calculating increasingly complex mathematic tables. Charles Babbage was a true Victorian era polymath. A lot was happening as the world awoke to a more scientific era and scientific publications grew in number and size. Born in London, Babbage loved math from an early age and went away to Trinity College in Cambridge in 1810. There he helped form the Analytical Society with John Herschel - a pioneer of early photography and a chemist and invented of the blueprint. And George Peacock, who established the British arm of algebraic logic, which when picked up by George Boole would go on to form part of Boolean algebra, ushering in the idea that everything can be reduced to a zero or a one. Babbage graduated from Cambridge and went on to become a Fellow of the Royal Society and helped found the Royal Astronomical Society. He published works with Herschel on electrodynamics that went on to be used by Michael Faraday later and even dabbled in actuarial tables - possibly to create a data driven insurance company. His father passed away in 1827, leaving him a sizable estate. And after applying multiple times he finally became a professor at Cambridge in 1828. He and the others from the Analytical Society were tinkering with things like generalized polynomials and what we think of today as a formal power series, all of which an be incredibly tedious and time consuming. Because it's iterative. Pascal and Leibnitz had pushed math forward and had worked on the engineering to automate various tasks, applying some of their science. This gave us Pascal's calculator and Leibnitz's work on information theory and his calculus ratiocinator added a stepped reckoner, now called the Leibniz wheel where he was able to perform all four basic arithmetic operations. Meanwhile, Babbage continued to bounce around between society, politics, science, mathematics, and even coining a book on manufacturing where he looked at rational design and profit sharing. He also looked at how tasks were handled and made observations about the skill level of each task and the human capital involved in carrying them out. Marx even picked up where Babbage left off and looked further into profitability as a motivator. He also invented the pilot for trains and was involved with lots of learned people of the day. Yet Babbage is best known for being the old, crusty gramps of the computer. Or more specifically the difference engine, which is different from a differential analyzer. A difference engine was a mechanical calculator that could perform polynomial functions. A differential analyzer on the other hand solves differential equations using wheels and disks. Babbage expanded on the ideas of Pascal and Leibniz and added to mechanical computing, making the difference engine, the inspiration of many a steampunk work of fiction. Babbage started work on the difference engine in 1819. Multiple engineers built different components for the engine and it was powered by a crank that spun a series of wheels, not unlike various clockworks available at the time. The project was paid for by the British Government who hoped it could save time calculating complex tables. Imagine doing all the work in spreadsheets manually. Each cell could take a fair amount of time and any mistake could be disastrous. But it was just a little before its time. The plans have been built and worked and while he did produce a prototype capable of raising numbers to the third power and perform some quadratic equations the project was abandoned in 1833. We'll talk about precision in a future episode. Again, the math involved in solving differential equations at the time was considerable and the time-intensive nature was holding back progress. So Babbage wasn't the only one working on such ideas. Gaspard-Gustave de Coriolis, known for the Coriolis effect, was studying the collisions of spheres and became a professor of mechanics in Paris. To aid in his works, he designed the first mechanical device to integrate differential equations in 1836. After Babbage scrapped his first, he moved on to the analytical engine, adding conditional branching, loops, and memory - and further complicating the machine. The engine borrowed the punchcard tech from the Jacquard loom and applied that same logic, along with the work of Leibniz, to math. The inputs would be formulas, much as Turing later described when concocting some of what we now call Artificial Intelligence. Essentially all problems could be solved given a formula and the output would be a printer. The analytical machine had 1,000 numbers worth of memory and a logic processor or arithmetic unit that he called a mill, which we'd call a CPU today. He even planned on a programming language which we might think of as assembly today. All of this brings us to the fact that while never built, it would have been a Turing-complete in that the simulation of those formulas was a Turing machine. Ada Lovelace contributed the concept of Bernoulli numbers in algorithms giving us a glimpse into what an open source collaboration might some day look like. And she was in many ways the first programmer - and daughter of Lord Byron and Anne Millbanke, a math whiz. She became fascinated with the engine and ended up becoming an expert at creating a set of instructions to punch on cards, thus the first programmer of the analytical engine and far before her time. In fact, there would be no programmer for 100 years with her depth of understanding. Not to make you feel inadequate, but she was 27 in 1843. Luigi Menabrea took the idea to France. And yet by the time Babbage died in 1871 without a working model. During those years, Per Georg Scheutz built a number of difference engines based on Babbage's published works - also funded by the government and would evolve to become the first calculator that could print. Martin Wiberg picked up from there and was able to move to 20 digit processing. George Grant at Harvard developed calculating machines and published his designs by 1876, starting a number of companies to fabricate gears along the way. James Thomson built a differential analyzer in 1876 to predict tides. And that's when his work on fluid dynamics and other technology seemed to be the connection between these machines and the military. Thomson's work would Joe added to work done by Arthur Pollen and we got our first automated fire-control systems. Percy Ludgate and Leonardo Torres wrote about Babbages work in the early years the 1900s and other branches of math needed other types of mechanical computing. Burroughs built a difference engine in 1912 and another in 1929. The differential analyzer was picked up by a number of scientists in those early years. But Vaneevar Bush was perhaps one of the most important. He, with Harold Locke Hazen built one at MIT and published an article on it in 1931. Here's where everything changes. The information was out there in academic journals. Bush published another in 1936 connecting his work to Babbage's. Bush's designs get used by a number of universities and picked up by the the Balistic Research Lab in the US. One of those installations was in the same basement ENIAC would be built in. Bush did more than inspire other mathematicians. Sometimes he paid them. His research assistant was Claude Shannon, who built the General Purpose Analog Computer in 1941 and went on to become founder of the whole concept of information theory, down to the bits to bytes. Shannon's computer was important as it came shortly after Alan Turing's work on Turing machines and so has been seen as a means to get to this concept of general, programmable computing - basically revisiting the Babbage concept of a thinking, or analytical machine. And Howard Aiken went a step further than mechanical computing and into electromechanical computing with he Mark I, where he referenced Babbage's work as well. Then we got the Atanasoff-Berry Computer in 1942. By then, our friend Bush had gone on to chair the National Defense Research Committee where he would serve under Roosevelt and Truman and help develop radar and the Manhattan Project as an administrator where he helped coordinate over 5,000 research scientists. Some helped with ENIAC, which was completed in 1945, thus beginning the era of programmable, digital, general purpose computers. Seeing how computers helped break Enigma machine encryption and solve the equations, blow up targets better, and solve problems that held science back was one thing - but unleashing such massive and instantaneous violence as the nuclear bomb caused Bush to write an article for The Atlantic called As We May Think, that inspired generations of computer scientists. Here he laid out the concept of a Memex, or a general purpose computer that every knowledge worker could have. And thus began the era of computing. What we wanted to look at in this episode is how Babbage wasn't an anomaly. Just as Konrad Zuse wasn't. People published works, added to the works they read about, cited works, pulled in concepts from other fields, and we have unbroken chains in our understanding of how science evolves. Some, like Konrad Zuse, might have been operating outside of this peer reviewing process - but he eventually got around to publishing as well.

Bob Tayler: ARPA to PARC to DEC

Play Episode Listen Later Jan 15, 2021 14:31

Robert Taylor was one of the true pioneers in computer science. In many ways, he is the string (or glue) that connected the US governments era of supporting computer science through ARPA to innovations that came out of Xerox PARC and then to the work done at Digital Equipment Corporation's Systems Research Center. Those are three critical aspects of the history of computing and while Taylor didn't write any of the innovative code or develop any of the tools that came out of those three research environments, he saw people and projects worth funding and made sure the brilliant scientists got what they needed to get things done. The 31 years in computing that his stops represented were some of the most formative years for the young computing industry and his ability to inspire the advances that began with Vannevar Bush's 1945 article called “As We May Think” then ended with the explosion of the Internet across personal computers. Bob Taylor inherited a world where computing was waking up to large crusty but finally fully digitized mainframes stuck to its eyes in the morning and went to bed the year Corel bought WordPerfect because PCs needed applications, the year the Pentium 200 MHz was released, the year Palm Pilot and eBay were founded, the year AOL started to show articles from the New York Times, the year IBM opened a we web shopping mall and the year the Internet reached 36 million people. Excite and Yahoo went public. Sometimes big, sometimes small, all of these can be traced back to Bob Taylor - kinda' how we can trace all actors to Kevin Bacon. But more like if Kevin Bacon found talent and helped them get started, by paying them during the early years of their careers… How did Taylor end up as the glue for the young and budding computing research industry? Going from tween to teenager during World War II, he went to Southern Methodist University in 1948, when he was 16. He jumped into the US Naval Reserves during the Korean War and then got his masters in psychology at the University of Texas at Austin using the GI Bill. Many of those pioneers in computing in the 60s went to school on the GI Bill. It was a big deal across every aspect of American life at the time - paving the way to home ownership, college educations, and new careers in the trades. From there, he bounced around, taking classes in whatever interested him, before taking a job at Martin Marietta, helping design the MGM-31 Pershing and ended up at NASA where he discovered the emerging computer industry. Taylor was working on projects for the Apollo program when he met JCR Licklider, known as the Johnny Appleseed of computing. Lick, as his friends called him, had written an article called Man-Computer Symbiosis in 1960 and had laid out a plan for computing that influenced many. One such person, was Taylor. And so it was in 1962 he began and in 1965 that he succeeded in recruiting Taylor away from NASA to take his place running ARPAs Information Processing Techniques Office, or IPTO. Taylor had funded Douglas Engelbart's research on computer interactivity at Stanford Research Institute while at NASA. He continued to do so when he got to ARPA and that project resulted in the invention of the computer mouse and the Mother of All Demos, one of the most inspirational moments and a turning point in the history of computing. They also funded a project to develop an operating system called Multics. This would be a two million dollar project run by General Electric, MIT, and Bell Labs. Run through Project MAC at MIT there were just too many cooks in the kitchen. Later, some of those Bell Labs cats would just do their own thing. Ken Thompson had worked on Multics and took the best and worst into account when he wrote the first lines of Unix and the B programming language, then one of the most important languages of all time, C. Interactive graphical computing and operating systems were great but IPTO, and so Bob Taylor and team, would fund straight out of the pentagon, the ability for one computer to process information on another computer. Which is to say they wanted to network computers. It took a few years, but eventually they brought in Larry Roberts, and by late 1968 they'd awarded an RFQ to build a network to a company called Bolt Beranek and Newman (BBN) who would build Interface Message Processors, or IMPs. The IMPS would connect a number of sites and route traffic and the first one went online at UCLA in 1969 with additional sites coming on frequently over the next few years. That system would become ARPANET, the commonly accepted precursor to the Internet. There was another networking project going on at the time that was also getting funding from ARPA as well as the Air Force, PLATO out of the University of Illinois. PLATO was meant for teaching and had begun in 1960, but by then they were on version IV, running on a CDC Cyber and the time sharing system hosted a number of courses, as they referred to programs. These included actual courseware, games, convent with audio and video, message boards, instant messaging, custom touch screen plasma displays, and the ability to dial into the system over lines, making the system another early network. Then things get weird. Taylor is sent to Vietnam as a civilian, although his rank equivalent would be a brigadier general. He helped develop the Military Assistance Command in Vietnam. Battlefield operations and reporting were entering the computing era. Only problem is, while Taylor was a war veteran and had been deep in the defense research industry for his entire career, Vietnam was an incredibly unpopular war and seeing it first hand and getting pulled into the theater of war, had him ready to leave. This combined with interpersonal problems with Larry Roberts who was running the ARPA project by then over Taylor being his boss even without a PhD or direct research experience. And so Taylor joined a project ARPA had funded at the University of Utah and left ARPA. There, he worked with Ivan Sutherland, who wrote Sketchpad and is known as the Father of Computer Graphics, until he got another offer. This time, from Xerox to go to their new Palo Alto Research Center, or PARC. One rising star in the computer research world was pretty against the idea of a centralized mainframe driven time sharing system. This was Alan Kay. In many ways, Kay was like Lick. And unlike the time sharing projects of the day, the Licklider and Kay inspiration was for dedicated cycles on processors. This meant personal computers. The Mansfield Amendment in 1973 banned general research by defense agencies. This meant that ARPA funding started to dry up and the scientists working on those projects needed a new place to fund their playtime. Taylor was able to pick the best of the scientists he'd helped fund at ARPA. He helped bring in people from Stanford Research Institute, where they had been working on the oNLineSystem, or NLS. This new Computer Science Laboratory landed people like Charles Thacker, David Boggs, Butler Lampson, and Bob Sproul and would develop the Xerox Alto, the inspiration for the Macintosh. The Alto though contributed the very ideas of overlapping windows, icons, menus, cut and paste, word processing. In fact, Charles Simonyi from PARC would work on Bravo before moving to Microsoft to spearhead Microsoft Word. Bob Metcalfe on that team was instrumental in developing Ethernet so workstations could communicate with ARPANET all over the growing campus-connected environments. Metcalfe would leave to form 3COM. SuperPaint would be developed there and Alvy Ray Smith would go on to co-found Pixar, continuing the work begun by Richard Shoup. They developed the Laser Printer, some of the ideas that ended up in TCP/IP, and the their research into page layout languages would end up with Chuck Geschke, John Warnock and others founding Adobe. Kay would bring us the philosophy behind the DynaBook which decades later would effectively become the iPad. He would also develop Smalltalk with Dan Ingalls and Adele Goldberg, ushering in the era of object oriented programming. They would do pioneering work on VLSI semiconductors, ubiquitous computing, and anything else to prepare the world to mass produce the technologies that ARPA had been spearheading for all those years. Xerox famously did not mass produce those technologies. And nor could they have cornered the market on all of them. The coming waves were far too big for one company alone. And so it was that PARC, unable to bring the future to the masses fast enough to impact earnings per share, got a new director in 1983 and William Spencer was yet another of three bosses that Taylor clashed with. Some resented that he didn't have a PhD in a world where everyone else did. Others resented the close relationship he maintained with the teams. Either way, Taylor left PARC in 1983 and many of the scientists left with him. It's both a curse and a blessing to learn more and more about our heroes. Taylor was one of the finest minds in the history of computing. His tenure at PARC certainly saw the a lot of innovation and one of the most innovative teams to have ever been assembled. But as many of us that have been put into a position of leadership, it's easy to get caught up in the politics. I am ashamed every time I look back and see examples of building political capital at the expense of a project or letting an interpersonal problem get in the way of the greater good for a team. But also, we're all human and the people that I've interviewed seem to match the accounts I've read in other books. And so Taylor's final stop was Digital Equipment Corporation where he was hired to form their Systems Research Center in Palo Alto. They brought us the AltaVista search engine, the Firefly computer, Modula-3 and a few other advances. Taylor retired in 1996 and DEC was acquired by Compaq in 1998 and when they were acquired by HP the SRC would get merged with other labs at HP. From ARPA to Xerox to Digital, Bob Taylor certainly left his mark on computing. He had a knack of seeing the forest through the trees and inspired engineering feats the world is still wrestling with how to bring to fruition. Raw, pure science. He died in 2017. He worked with some of the most brilliant people in the world at ARPA. He inspired passion, and sometimes drama in what Stanford's Donald Knuth called “the greatest by far team of computer scientists assembled in one organization.” In his final email to his friends and former coworkers, he said “You did what they said could not be done, you created things that they could not see or imagine.” The Internet, the Personal Computer, the tech that would go on to become Microsoft Office, object oriented programming, laser printers, tablets, ubiquitous computing devices. So, he isn't exactly understating what they accomplished in a false sense of humility. I guess you can't do that often if you're going to inspire the way he did. So feel free to abandon the pretense as well, and go inspire some innovation. Heck, who knows where the next wave will come from. But if we aren't working on it, it certainly won't come. Thank you so much and have a lovely, lovely day. We are so lucky to have you join us on yet another episode.

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Claude Shannon and the Origins of Information Theory

Play Episode Listen Later Sep 9, 2020 11:27

The name Claude Shannon has come up 8 times so far in this podcast. More than any single person. We covered George Boole and the concept that Boolean is a 0 and a 1 and that using Boolean algebra, you can abstract simple circuits into practically any higher level concept. And Boolean algebra had been used by a number of mathematicians, to perform some complex tasks. Including by Lewis Carroll in Through The Looking Glass to make words into math. And binary had effectively been used in morse code to enable communications over the telegraph. But it was Claude Shannon who laid the foundation for making a theory that took both the concept of communicating over the telegraph and applying Boolean algebra to get to a higher level of communication possible. And it all starts with bits, which we can thank Shannon for. Shannon grew up in Gaylord, Michigan. His mother was a high school principal and his grandfather had been an inventor. He built a telegraph as a child, using a barbed wire fence. But barbed wire isn't the greatest conducer of electricity and so… noise. And thus information theory began to ruminate in his mind. He went off to the University of Michigan and got a Bachelors in electrical engineering and another in math. A perfect combination for laying the foundation of the future. And he got a job as a research assistant to Vannevar Bash, who wrote the seminal paper, As We May Think. At that time, Bush was working at MIT on The Thinking Machine, or Differential Analyzer. This was before World War II and they had no idea, but their work was about to reshape everything. At the time, what we think of as computers today, were electro-mechanical. They had gears that were used for the more complicated tasks, and switches, used for simpler tasks. Shannon devoted his masters thesis to applying Boolean algebra, thus getting rid of the wheels, which moved slowly, and allowing the computer to go much faster. He broke down Boole's Laws of Thought into a manner it could be applied to parallel circuitry. That paper was called A Symbolic Analysis of Relay and Switching Circuits in 1937 and helped set the stage for the Hackers revolution that came shortly thereafter at MIT. At the urging of Vannevar Bush, he got his PhD in Biology, pushing genetics forward by theorizing that you could break the genetic code down into a matrix. The structure of DNA would be discovered by George Gamow in 1953 and Watson and Crick would discover the helix and Rosalind Franklin would use X-ray crystallography to capture the first photo of the structure. He headed off to Princeton in 1940 to work at the Institute for Advanced Study, where Einstein and von Neumann were. He quickly moved over to the National Defense Research Committee, as the world was moving towards World War II. A lot of computing was going into making projectiles, or bombs, more accurate. He co-wrote a paper called Data Smoothing and Prediction in Fire-Control Systems during the war. He'd gotten a primer in early cryptography, reading The Gold-Bug by Edgar Allan Poe as a kid. And it struck his fancy. So he started working on theories around cryptography, everything he'd learned forming into a single theory. He would have lunch with Alan Turning during the war. He would And it was around this work that he first coined the term “information theory” in 1945. A universal theory of communication gnawed at him and formed during this time, from the Institute, to the National Defense Research Committee, to Bell Labs, where he helped encrypt communications between world leaders. He hid it from everyone, including failed relationships. He broke information down into the smallest possible unit, a bit, short for a binary digit. He worked out how to compress information that was most repetitive. Similar to how morse code compressed the number of taps on the electrical wire by making the most common letters the shortest to send. Eliminating redundant communications established what we now call compression. Today we use the term lossless compression frequently in computing. He worked out that the minimum amount of information to send would be H = - Sigma Pi log2 Pi - or entropy. His paper, put out while he was at Bell, was called “A mathematical theory or communication” and came out in 1948. You could now change any data to a zero or a one and then compress it. Further, he had to find a way to calculate the maximum amount of information that could be sent over a communication channel before it became garbled, due to loss. We now call this the Shannon Limit. And so once we have that, he derived how to analyze information with math to correct for noise. That barbed wire fence could finally be useful. This would be used in all modern information connectivity. For example, when I took my Network+ we spent an inordinate amount of time learning about Carrier-sense multiple access with collision detection (CSMA/CD) - a media access control (MAC) method that used carrier-sensing to defer transmissions until no other stations are transmitting. And as his employer, Bell Labs helped shape the future of computing. Along with Unix, C, C++, the transistor, the laser, information theory is a less tangible yet given what we all have in our pockets on on our wrists these days, more tangible discovery. Having mapped the limits, Bell started looking to reach the limit. And so the digital communication age was born when the first modem would come out of his former employer, Bell Labs, in 1958. And just across the way in Boston, ARPA would begin working on the first Interface Message Processor in 1967, the humble beginnings of the Internet. His work done, he went back to MIT. His theories were applied to all sorts of disciplines. But he comes in less and less. Over time we started placing bits on devices. We started retrieving those bits. We started compressing data. Digital images, audio, and more. It would take 35 or so years He consulted with the NSA on cryptography. In 1949 he published Communication Theory of Secrecy Systems, pushed cryptography to the next level. His paper Prediction and Entropy of Printed English in 1951 practically created the field of natural language processing, which evolved into various branches of machine learning. He helped give us the Nyquist–Shannon sampling theorem, used in aliasing, deriving maximum throughput, RGB, and of course signal to noise. He loved games. In 1941 he theorized the Shannon Number, or the game-tree complexity of chess. In case you're curious, the reason deep blue can win at chess is that it can brute force 10 to the 120th power. His love of games continued and in 1949 he presented Programming a Computer for Playing Chess. That was the first time we thought about computers playing chess. And he'd have a standing bet that a computer would beat a human grand master at chess by 2001. Garry Kasparov lost to Deep Blue in 1997. That curiosity extended far beyond chess. He would make Theseus in 1950 - a maze with a mouse that learned how to escape, using relays from phone switches. One of the earliest forms of machine learning. In 1961 he would co-invent the first wearable computer to help win a game of roulette. That same year he designed the Minivan 601 to help teach how computers worked. So we'll leave you with one last bit of information. Shannon's maxim is that “the enemy knows the system.” I used to think it was just a shortened version of Kerckhoffs's principle, which is that it should be possible to understand a cryptographic system, for example, modern public key ciphers, but not be able to break the encryption without a private key. Thing is, the more I know about Shannon the more I suspect that what he was really doing was giving the principle a broader meaning. So think about that as you try and decipher what is and what is not disinformation in such a noisy world. Lots and lots of people would cary on the great work in information theory. Like Kullback–Leibler divergence, or relative entropy. And we owe them all our thanks. But here's the thing about Shannon: math. He took things that could have easily been theorized - and he proved them. Because science can refute disinformation. If you let it.

Sketchpad

Play Episode Listen Later Jul 13, 2020 6:31

Welcome to the History of Computing Podcast, where we explore the history of information technology. Because understanding the past prepares us to innovate (and sometimes cope with) the future! Today we're going to cover yet another of the groundbreaking technologies to come out of MIT: Sketchpad. Ivan Sutherland is a true computer scientist. After getting his masters from Caltech, he migrated to the land of the Hackers and got a PhD from MIT in 1963. The great Claud Shannon supervised his thesis and Marvin Minsky was on the thesis review committee. But he wasn't just surrounded by awesome figures in computer science, he would develop a critical piece between the Memex in Vannevar Bush's “As We May Think” and the modern era of computing: graphics. What was it that propelled him from PhD candidate to becoming the father of computer graphics? The 1962-1963 development of a program called Sketchpad. Sketchpad was the ancestor of the GUI, object oriented programming, and computer graphics. In fact, it was the first graphical user interface. And it was all made possible by the TX-2, a computer developed at the MIT Lincoln Laboratory by Wesley Clark and others. The TX-2 was transistorized and so fast. Fast enough to be truly interactive. A lot of innovative work had come with the TX-0 and the program would effectively spin off as Digital Equipment Corporation and the PDP series of computers. So it was bound to inspire a lot of budding computer scientists to build some pretty cool stuff. Sutherland's Sketchpad used a light pen. These were photosensitive devices that worked like a stylus but would send light to the display, activating dots on a cathode ray tube (CRT). Users could draw shapes on a screen for the first time. Whirlwind at MIT had allowed highlighting objects, but this graphical interface to create objects was a new thing altogether, inputing data into a computer as an object instead of loading it as code, as could then be done using punch cards. Suddenly the computer could be used for art. There were toggle-able switches that made lines bigger. The extra memory that was pretty much only available in the hallowed halls of government-funded research in the 60s opened up so many possibilities. Suddenly, computer-aided design, or CAD, was here. Artists could create a master drawing and then additional instances on top, with changes to the master reverberating through each instance. They could draw lines, concentric circles, change ratios. And it would be 3 decades before MacPaint would bring the technology into homes across the world. And of course AutoCAD, making Autodesk one of the greatest software companies in the world. The impact of Sketchpad would be profound. Sketchpad would be another of Doug Englebart's inspirations when building the oN-Line System and there are clear correlations in the human interfaces. For more on NLS, check out the episode of this podcast called the Mother of All Demos, or watch it on YouTube. And Sutherland's work would inspire the next generation: people who read his thesis, as well as his students and coworkers. Sutherland would run the Information Processing Techniques Office for the US Defense Department Advanced Research Project Agency after Lick returned to MIT. He also taught at Harvard, where he and students developed the first virtual reality system in 1968, decades before it was patented by VPL research in 1984. Sutherland then went to the University of Utah, where he taught Alan Kay who gave us object oriented programming in smalltalk and the concept of the tablet in the Dynabook, and Ed Catmull who co-founded Pixar and many other computer graphics pioneers. He founded Evans and Sutherland, with the man that built the computer science department at the University of Utah and their company launched the careers of John Warnock, the founder of Adobe and Jim Clark, the founder of Silicon Graphics. His next company would be acquired by Sun Microsystems and become Sun Labs. He would remain a Vice President and fellow at Sun and a visiting scholar at Berkeley. For Sketchpad and his other contributions to computing, he would be awarded a Computer Pioneer Award, become a fellow at the ACM, receive a John von Neumann Medal, receive the Kyoto Prize, become a fellow at the Computer History Museum, and receive a Turing Award. I know we're not supposed to make a piece of software an actor in a sentence, but thank you Sketchpad. And thank you Sutherland. And his students and colleagues who continued to build upon his work.

university history mother phd vice president mit utah harvard sun tx artists pixar evans hackers berkeley adobe users crt cad lick sutherland whirlwind caltech autodesk acm sun microsystems pdp ed catmull autocad jim clark nls wesley clark turing award computer history museum silicon graphics alan kay marvin minsky digital equipment corporation vpl kyoto prize sketchpad john warnock all demos memex ivan sutherland macpaint as we may think

As We May Think and the Legacy of Vannevar Bush

Play Episode Listen Later Mar 21, 2020 7:14

Today we're going to celebrate an article called As We May Think and it's author, Vannevar Bush. Imagine it's 1945. You see the future and prognosticate instant access to all of the information in the world from a device that sits on every person's desk at their office. Microfiche wouldn't come along for another 14 years. But you see the future. And the modern interpretations of this future would be the Internet and personal computing. But it's 1945. There is no transistor and no miniaturization that led to microchips. But you've seen ENIAC and you see a path ahead and know where the world is going. And you share it. That is exactly what happened in “As We May Think” an article published by Vannevar Bush in The Atlantic. Vannevar Bush was one of the great minds in early computing. He got his doctorate from MIT and Harvard in 1916 and went into the private sector. During World War I he built a submarine detector and went back to MIT splitting his time between academic pursuits, inventing, and taking inventions to market. He worked with American Radio and Research Corporation (AMRAD), made millions off an early thermostat company, and founded the American Appliance Company, now known as the defense contracting powerhouse Raytheon. By 1927 computing began to tickle his fancy and he built a differential analyzer, or a mechanical computer to do all the maths! He would teach at MIT penning texts on circuit design and his work would influence the great Claude Shannon and his designs would be used in early codebreaking computers. He would become a Vice President of MIT as well as the Dean of the MIT School of Engineering. Then came World War II. He went to work at the Carnegie Institute of Science, where he was exposed to even more basic research than during his time with MIT. Then he sat on and chaired the National Advisory Committee for Aeronautics, which would later become NASA - helping you get the Ames Research Crnter and Glenn Research Center started. Seems like a full career? Nah, just getting started! he went to President Roosevelt and got the National Defense Research Committee approved. There, they developed antiaircraft guns, radar, and funded the development of ENIAC. Roosevelt then made him head of the Office of Scientific Research and Development who worked on developing the proximity fuse. There he also recruited Robert Oppenheimer to run the Manhattan Project and was there in 1945 for the Trinity Test, to see the first nuclear bomb detonated. And that is when he lost a major argument. Rather than treat nuclear weapons like the international community had treated biological weapons, the world would enter into a nuclear arms race. We still struggle with that fallout today. He would publish As We May Think in the Atlantic that year and inspire the post World War II era of computing in a few ways. The first is funding. He was the one behind the National Science Foundation. And he advised a lot of companies and US government agencies on R&D through his remaining years sitting on boards, acting as a trustee, and even a regent of the Smithsonian. Another was inspiration. As We May Think laid out a vision. Based on all of the basic and applied research he had been exposed to, he was able to see the convergence that would come decades later. ENIAC would usher in the era of mainframes. But things would get smaller. Cameras and microfilm and the parsing of data would put more information at our fingertips than ever. An explosion of new information out of all of this research would follow and we would need to parse it using those computers, which he called a memex. The collective memory of the world. But he warned of an arms race leading to us destroying the world first. Ironically it was the arms race that in many ways caused Bush's predictions to come true. The advances made in computing during the Cold War were substantial. The arms race wasn't just about building bigger and more deadly nuclear weapons but brought us into the era of transistorized computing and then minicomputers and of course ARPANET. And then around the time that basic research was getting defunded by the government due to Vietnam the costs had come down enough to allow Commodore, Apple, and Radioshack to flood the market with inexpensive computers and for the nets to be merged into the Internet. And the course we are on today was set. I can almost imagine Bush sitting in a leather chair in 1945 trying to figure out if the powers of creation or the powers of destruction would win the race to better technology. And I'm still a little curious to see how it all turns out. The part of his story that is so compelling is information. He predicted that machines would help unlock even faster research, let us make better decisions, and ultimately elevate the human consciousness. Doug Englebart saw it. The engineers at Xerox saw it. Steve Jobs made it accessible to all of us. And we should all look to further that cause. Thank you for tuning in to yet another episode of the History of Computing Podcast. We are so very lucky to have you.

The Mouse

Play Episode Listen Later Feb 18, 2020 18:26

In a world of rapidly changing technologies, few have lasted as long is as unaltered a fashion as the mouse. The party line is that the computer mouse was invente d by Douglas Engelbart in 1964 and that it was a one-button wooden device that had two metal wheels. Those used an analog to digital conversion to input a location to a computer. But there's a lot more to tell. Englebart had read an article in 1945 called “As We May Think” by Vannevar Bush. He was in the Philippines working as a radio and radar tech. He'd return home,. Get his degree in electrical engineering, then go to Berkeley and get first his masters and then a PhD. Still in electrical engineering. At the time there were a lot of military grants in computing floating around and a Navy grant saw him work on a computer called CALDIC, short for the California Digital Computer. By the time he completed his PhD he was ready to start a computer storage company but ended up at the Stanford Research Institute in 1957. He published a paper in 1962 called Augmenting Human Intellect: A Conceptual Framework. That paper would guide the next decade of his life and help shape nearly everything in computing that came after. Keeping with the theme of “As We May Think” Englebart was all about supplementing what humans could do. The world of computer science had been interested in selecting things on a computer graphically for some time. And Englebart would have a number of devices that he wanted to test in order to find the best possible device for humans to augment their capabilities using a computer. He knew he wanted a graphical system and wanted to be deliberate about every aspect in a very academic fashion. And a key aspect was how people that used the system would interact with it. The keyboard was already a mainstay but he wanted people pointing at things on a screen. While Englebart would invent the mouse, pointing devices certainly weren't new. Pilots had been using the joystick for some time, but an electrical joystick had been developed at the US Naval Research Laboratory in 1926, with the concept of unmanned aircraft in mind. The Germans would end up building one in 1944 as well. But it was Alan Kotok who brought the joystick to the computer game in the early 1960s to play spacewar on minicomputers. And Ralph Baer brought it into homes in 1967 for an early video game system, the Magnavox Odyssey. Another input device that had come along was the trackball. Ralph Benjamin of the British Royal Navy's Scientific Service invented the trackball, or ball tracker for radar plotting on the Comprehensive Display System, or CDS. The computers were analog at the time but they could still use the X-Y coordinates from the trackball, which they patented in 1947. Tom Cranston, Fred Longstaff and Kenyon Taylor had seen the CDS trackball and used that as the primary input for DATAR, a radar-driven battlefield visualization computer. The trackball stayed in radar systems into the 60s, when Orbit Instrument Corporation made the X-Y Ball Tracker and then Telefunken turned it upside down to control the TR 440, making an early mouse type of device. The last of the options Englebart decided against was the light pen. Light guns had shown up in the 1930s when engineers realized that a vacuum tube was light-sensitive. You could shoot a beam of light at a tube and it could react. Robert Everett worked with Jay Forrester to develop the light pen, which would allow people to interact with a CRT using light sensing to cause an interrupt on a computer. This would move to the SAGE computer system from there and eek into the IBM mainframes in the 60s. While the technology used to track the coordinates is not even remotely similar, think of this as conceptually similar to the styluses used with tablets and on Wacom tablets today. Paul Morris Fitts had built a model in 1954, now known as Fitts's Law, to predict the time that's required to move things on a screen. He defined the target area as a function of the ratio between the distance to the target and the width of the target. If you listen to enough episodes of this podcast, you'll hear a few names repeatedly. One of those is Claude Shannon. He brought a lot of the math to computing in the 40s and 50s and helped with the Shannon-Hartley Theorum, which defined information transmission rates over a given medium. So these were the main options at Englebart's disposal to test when he started ARC. But in looking at them, he had another idea. He'd sketched out the mouse in 1961 while sitting in a conference session about computer graphics. Once he had funding he brought in Bill English to build a prototype I n 1963. The first model used two perpendicular wheels attached to potentiometers that tracked movement. It had one button to select things on a screen. It tracked x,y coordinates as had previous devices. NASA funded a study to really dig in and decide which was the best device. He, Bill English, and an extremely talented team, spent two years researching the question, publishing a report in 1965. They really had the blinders off, too. They looked at the DEC Grafacon, joysticks, light pens and even what amounts to a mouse that was knee operated. Two years of what we'd call UX research or User Research today. Few organizations would dedicate that much time to study something. But the result would be patenting the mouse in 1967, an innovation that would last for over 50 years. I've heard Engelbart criticized for taking so long to build the oNline System, or NLS, which he showcased at the Mother of All Demos. But it's worth thinking of his research as academic in nature. It was government funded. And it changed the world. His paper on Computer-Aided Display Controls was seminal. Vietnam caused a lot of those government funded contracts to dry up. From there, Bill English and a number of others from Stanford Research Institute which ARC was a part of, moved to Xerox PARC. English and Jack Hawley iterated and improved the technology of the mouse, ditching the analog to digital converters and over the next few years we'd see some of the most substantial advancements in computing. By 1981, Xerox had shipped the Alto and the Star. But while Xerox would be profitable with their basic research, they would miss something that a candle-clad hippy wouldn't. In 1979, Xerox let Steve Jobs make three trips to PARC in exchange for the opportunity to buy 100,000 shares of Apple stock pre-IPO. The mouse by then had evolved to a three button mouse that cost $300. It didn't roll well and had to be used on pretty specific surfaces. Jobs would call Dean Hovey, a co-founder of IDEO and demand they design one that would work on anything including quote “blue jeans.” Oh, and he wanted it to cost $15. And he wanted it to have just one button, which would be an Apple hallmark for the next 30ish years. Hovey-Kelley would move to optical encoder wheels, freeing the tracking ball to move however it needed to and then use injection molded frames. And thus make the mouse affordable. It's amazing what can happen when you combine all that user research and academic rigor from Englebarts team and engineering advancements documented at Xerox PARC with world-class industrial design. You see this trend played out over and over with the innovations in computing that are built to last. The mouse would ship with the LISA and then with the 1984 Mac. Logitech had shipped a mouse in 1982 for $300. After leaving Xerox, Jack Howley founded a company to sell a mouse for $400 the same year. Microsoft released a mouse for $200 in 1983. But Apple changed the world when Steve Jobs demanded the mouse ship with all Macs. The IBM PC would ;use a mouse and from there it would become ubiquitous in personal computing. Desktops would ship with a mouse. Laptops would have a funny little button that could be used as a mouse when the actual mouse was unavailable. The mouse would ship with extra buttons that could be mapped to additional workflows or macros. And even servers were then outfitted with switches that allowed using a device that switched the keyboard, video, and mouse between them during the rise of large server farms to run the upcoming dot com revolution. Trays would be put into most racks with a single u, or unit of the rack being used to see what you're working on; especially after Windows or windowing servers started to ship. As various technologies matured, other innovations came along to input devices. The mouse would go optical in 1980 and ship with early Xerox Star computers but what we think of as an optical mouse wouldn't really ship until 1999 when Microsoft released the IntelliMouse. Some of that tech came to them via Hewlett-Packard through the HP acquisition of DEC and some of those same Digital Research Institute engineers had been brought in from the original mainstreamer of the mouse, PARC when Bob Taylor started DRI. The LED sensor on the muse stuck around. And thus ended the era of the mouse pad, once a hallmark of many a marketing give-away. Finger tracking devices came along in 1969 but were far too expensive to produce at the time. As capacitive sensitive pads, or trackpads came down in price and the technology matured those began to replace the previous mouse-types of devices. The 1982 Apollo computers were the first to ship with a touchpad but it wasn't until Synaptics launched the TouchPad in 1992 that they began to become common, showing up in 1995 on Apple laptops and then becoming ubiquitous over the coming years. In fact, the IBM Thinkpad and many others shipped laptops with little red nubs in the keyboard for people that didn't want to use the TouchPad for awhile as well. Some advancements in the mouse didn't work out. Apple released the hockey puck shaped mouse in 1998, when they released the iMac. It was USB, which replaced the ADB interface. USB lasted. The shape of the mouse didn't. Apple would go to the monolithic surface mouse in 2000, go wireless in 2003 and then release the Mighty Mouse in 2005. The Mighty Mouse would have a capacitive touch sensor and since people wanted to hear a click would produce that with a little speaker. This also signified the beginning of bluetooth as a means of connecting a mouse. Laptops began to replace desktops for many, and so the mouse itself isn't as dominant today. And with mobile and tablet computing, resistive touchscreens rose to replace many uses for the mouse. But even today, when I edit these podcasts, I often switch over to a mouse simply because other means of dragging around timelines simply aren't as graceful. And using a pen, as Englebart's research from the 60s indicated, simply gets fatiguing. Whether it's always obvious, we have an underlying story we're often trying to tell with each of these episodes. We obviously love unbridled innovation and a relentless drive towards a technologically utopian multiverse. But taking a step back during that process and researching what people want means less work and faster adoption. Doug Englebart was a lot of things but one net-new point we'd like to make is that he was possibly the most innovative in harnessing user research to make sure that his innovations would last for decades to come. Today, we'd love to research every button and heat map and track eyeballs. But remembering, as he did, that our job is to augment human intellect, is best done when we make our advances useful, helps to keep us and the forks that occur in technology from us, from having to backtrack decades of work in order to take the next jump forward. We believe in the reach of your innovations. So next time you're working on a project. Save yourself time, save your code a little cyclomatic complexity, , and save users frustration from having to relearn a whole new thing. And research what you're going to do first. Because you never know. Something you engineer might end up being touched by nearly every human on the planet the way the mouse has. Thank you Englebart. And thank you to NASA and Bob Roberts from ARPA for funding such important research. And thank you to Xerox PARC, for carrying the torch. And to Steve Jobs for making the mouse accessible to every day humans. As with many an advance in computing, there are a lot of people that deserve a little bit of the credit. And thank you listeners, for joining us for another episode of the history of computing podcast. We're so lucky to have you. Now stop consuming content and go change the world.

history english apple mother law phd german microsoft jobs nasa vietnam navy mac computers philippines windows ibm apollo led berkeley steve jobs finger ipo mouse cds arc ux hp laptops alto usb pilots crt macs desktops parc hewlett packard imac xerox logitech ideo xy arpa mighty mouse user research dri wacom fitts adb trays bob roberts nls british royal navy ibm pc claude shannon xerox parc bob taylor stanford research institute touchpad bill english magnavox odyssey douglas engelbart telefunken synaptics all demos online system engelbart jack hawley intellimouse as we may think

Smalltalk and Object-Oriented Programming

Play Episode Listen Later Sep 29, 2019 12:22

Welcome to the History of Computing Podcast, where we explore the history of information technology. Because understanding the past prepares us for the innovations of the future! Today we're going to cover the first real object-oriented programming language, Smalltalk. Many people outside of the IT industry would probably know the terms Java, Ruby, or Swift. But I don't think I've encountered anyone outside of IT that has heard of Smalltalk in a long time. And yet… Smalltalk influenced most languages in use today and even a lot of the base technologies people would readily identify with. As with PASCAL from Episode 3 of the podcast, Smalltalk was designed and created in part for educational use, but more so for constructionist learning for kids. Smalltalk was first designed at the Learning Research Group (LRG) of Xerox PARC by Alan Kay, Dan Ingalls, Adele Goldberg, Ted Kaehler, Scott Wallace, and others during the 1970s. Alan Kay had coined the term object-oriented programming was coined by Alan Kay in the late 60s. Kay took the lead on a project which developed an early mobile device called the Dynabook at Xerox PARC, as well as the Smalltalk object-oriented programming language. The first release was called Smalltalk-72 and was really the first real implementation of this weird new programming philosophy Kay had called object-oriented programming. Although… Smalltalk was inspired by Simula 67, from Norwegian developers Kirsten Nygaard and Ole-johan Dahl. Even before that Stewart Nelson and others from MIT had been using a somewhat object oriented model when working on Lisp and other programs. Kay had heard of Simula and how it handled passing messages and wrote the initial Smalltalk in a few mornings. He'd go on work with Dan Ingalls to help with implementation and Adele Goldberg to write documentation. This was Smalltalk 71. Object oriented program is a programming language model where programs are organized around data, also called objects. This is a contrast to programs being structured around functions and logic. Those objects could be data fields, attributes, behaviors, etc. For example, a product you're selling can have a sku, a price, dimensions, quantities, etc. This means you figure out what objects need to be manipulated and how those objects interact with one another. Objects are generalized as a class of objects. These classes define the kind of data and the logic used when manipulating data. Within those classes, there are methods, which define the logic and interfaces for object communication, known as messages. As programs grow and people collaborate on them together, an object-oriented approach allows projects to more easily be divided up into various team members to work on different parts. Parts of the code are more reusable. The way programs are played out is more efficient. And in turn, the code is more scalable. Object-oriented programming is based on a few basic principals. These days those are interpreted as encapsulation, abstraction, inheritance, and polymorphism. Although to Kay encapsulation and messaging are the most important aspects and all the classing and subclassing isn't nearly as necessary. Most modern languages that matter are based on these same philosophies, such as java, javascript, Python, C++, .Net, Ruby. Go, Swift, etc. Although Go is arguably not really object-oriented because there's no type hierarchy and some other differences, but when I look at the code it looks object-oriented! So there was this new programming paradigm emerging and Alan Kay really let it shine in Smalltalk. At the time, Xerox PARC was in the midst of revolutionizing technology. The MIT hacker ethic had seeped out to the west coast with Marvin Minsky's AI lab SAIL at Stanford and got all mixed into the fabric of chip makers in the area, such as Fairchild. That Stanford connection is important. The Augmentation Research Center is where Engelbart introduced the NLS computer and invented the Mouse there. And that work resulted in advances like hypertext links. In the 60s. Many of those Stanford Research Institute people left for Xerox PARC. Ivan Sutherland's work on Sketchpad was known to the group, as was the mouse from NLS, and because the computing community that was into research was still somewhat small, most were also aware of the graphic input language, or GRAIL, that had come out of Rand. Sketchpad's had handled each drawing elements as an object, making it a predecessor to object-oriented programming. GRAIL ran on the Rand Tablet and could recognize letters, boxes, and lines as objects. Smalltalk was meant to show a dynamic book. Kinda' like the epub format that iBooks uses today. The use of similar objects to those used in Sketchpad and GRAIL just made sense. One evolution led to another and another, from Lisp and the batch methods that came before it through to modern models. But the Smalltalk stop on that model railroad was important. Kay and the team gave us some critical ideas. Things like overlapping windows. These were made possibly by the inheritance model of executions, a standard class library, and a code browser and editor. This was one of the first development environments that looked like a modern version of something we might use today, like an IntelliJ or an Eclipse for Java developers. Smalltalk was the first implementation of the Model View Controller in 1979, a pattern that is now standard for designing graphical software interfaces. MVC divides program logic into the Model, the View, and the Controller in order to separate internal how data is represented from how it is presented as decouples the model from the view and the controller allow for much better reuse of libraries of code as well as much more collaborative development. Another important thing happened at Xerox in 1979, as they were preparing to give Smalltalk to the masses. There are a number of different interpretations to stories about Steve Jobs and Xerox PARC. But in 1979, Jobs was looking at how Apple would evolve. Andy Hertzfeld and the original Mac team were mostly there at Apple already but Jobs wanted fresh ideas and traded a million bucks in Apple stock options to Xerox for a tour of PARC. The Lisa team came with him and got to see the Alto. The Alto prototype was part of the inspiration for a GUI-based Lisa and Mac, which of course inspired Windows and many advances since. Smalltalk was finally released to other vendors and institutions in 1980, including DEC, HP, Apple, and Berkely. From there a lot of variants have shown up. Instantiations partnered with IBM and in 1984 had the first commercial version at Tektronix. A few companies tried to take SmallTalk to the masses but by the late 80s SQL connectivity was starting to add SQL support. The Smalltalk companies often had names with object or visual in the name. This is a great leading indicator of what Smalltalk is all about. It's visual and it's object oriented. Those companies slowly merged into one another and went out of business through the 90s. Instantiations was acquired by Digitalk. ParcPlace owed it's name to where the language was created. The biggest survivor was ObjectShare, who was traded on NASDAQ, peaking at $24 a share until 1999. In a LA Times article: “ObjectShare Inc. said its stock has been delisted from the Nasdaq national market for failing to meet listing requirements. In a press release Thursday, the company said it is appealing the decision.” And while the language is still maintained by companies like Instantiations, in the heyday, there was even a version from IBM called IBM VisualAge Smalltalk. And of course there were combo-language abominations, like a smalltalk java add on. Just trying to breathe some life in. This was the era where Filemaker, Foxpro, and Microsoft Access were giving developers the ability to quickly build graphical tools for managing data that were the next generation past what Smalltalk provided. And on the larger side products like JDS, Oracle, Peoplesoft, really jumped to prominence. And on the education side, the industry segmented into learning management systems and various application vendors. Until iOS and Google when apps for those platforms became all the rage. Smalltalk does live on in other forms though. As with many dying technologies, an open source version of Smalltalk came along in 1996. Squeak was written by Alan Kay, Dan Ingalls, Ted Kaehler, Scott Wallace, John Maloney, Andreas Raab, Mike Rueger and continues today. I've tinkerated with Squeak here and there and I have to say that my favorite part is just getting to see how people who actually truly care about teaching languages to kids. And how some have been doing that for 40 years. A great quote from Alan Kay, discussing a parallel between Vannevar Bush's “As We May Think” and the advances they made to build the Dynabook: If somebody just sat down and implemented what Bush had wanted in 1945, and didn't try and add any extra features, we would like it today. I think the same thing is true about what we wanted for the Dynabook. There's a direct path with some of the developers of Smalltalk to deploying MacBooks and Chromebooks in classrooms. And the influences these more mass marketed devices have will be felt for generations to come. Even as we devolve to new models from object-oriented programming, and new languages. The research that went into these early advances and the continued adoption and research have created a new world of teaching. At first we just wanted to teach logic and fundamental building blocks. Now kids are writing code. This might be writing java programs in robotics classes, html in Google Classrooms, or beginning iOS apps in Swift Playgrounds. So until the next episode, think about this: Vannevar Bush pushed for computers to help us think, and we have all of the worlds data at our fingertips. With all of the people coming out of school that know how to write code today, with the accelerometers, with the robotics skills, what is the next stage of synthesizing all human knowledge and truly making computers help with As we may think. So thank you so very much for tuning into another episode of the History of Computing Podcast. We're lucky to have you. Have a great day!

08 - Algorithmes - PDF

Play Episode Listen Later Jan 31, 2018 53:01

Claire Mathieu Collège de France Informatique et sciences numériques (2017-2018) partenariat Inria Algorithmes Bibliographie Les numéros de pages font référence aux diapositives utilisées pour le cours. p. 4-13 et p. 22 Easley D. et Kleinberg J., "Networks, Crowds, and Markets: Reasoning About a Highly Connected World" Sections 13.1 et 13.2 Accéder au site p. 7-13 Bush V., "As We May Think", juillet 1945 Accéder au site p. 15-20 Easley-Kleinberg, Section 18.7 p. 23-29 Kanade V., Levi R., Lotker Z., Mallmann-Trenn F., Mathieu C., "Distance in the Forest Fire Model: How far are you from Eve?", ACM-SIAM SODA (Symposium on Discrete Algorithms), 2016 Accéder au PDF p. 30-39 Avin C., Keller B., Lotker Z., Mathieu C., Peleg D., Pignolet Y.-A., "Homophily and the Glass Ceiling Effect in Social Networks", ITCS (Innovations in Theoretical Computer Science), 2015 Accéder au PDF p. 41 Easley-Kleinberg, Section 16.2

distance networks crowds social networks algorithmes homophily theoretical computer science mathieu c as we may think

08 - Algorithmes - VIDEO

Play Episode Listen Later Jan 31, 2018 53:01

Claire Mathieu Collège de France Informatique et sciences numériques (2017-2018) partenariat Inria Algorithmes Bibliographie Les numéros de pages font référence aux diapositives utilisées pour le cours. p. 4-13 et p. 22 Easley D. et Kleinberg J., "Networks, Crowds, and Markets: Reasoning About a Highly Connected World" Sections 13.1 et 13.2 Accéder au site p. 7-13 Bush V., "As We May Think", juillet 1945 Accéder au site p. 15-20 Easley-Kleinberg, Section 18.7 p. 23-29 Kanade V., Levi R., Lotker Z., Mallmann-Trenn F., Mathieu C., "Distance in the Forest Fire Model: How far are you from Eve?", ACM-SIAM SODA (Symposium on Discrete Algorithms), 2016 Accéder au PDF p. 30-39 Avin C., Keller B., Lotker Z., Mathieu C., Peleg D., Pignolet Y.-A., "Homophily and the Glass Ceiling Effect in Social Networks", ITCS (Innovations in Theoretical Computer Science), 2015 Accéder au PDF p. 41 Easley-Kleinberg, Section 16.2

distance networks crowds social networks algorithmes homophily theoretical computer science mathieu c as we may think

08 - Algorithmes - VIDEO

Play Episode Listen Later Jan 31, 2018 53:01

Claire Mathieu Collège de France Informatique et sciences numériques (2017-2018) partenariat Inria Algorithmes Bibliographie Les numéros de pages font référence aux diapositives utilisées pour le cours. p. 4-13 et p. 22 Easley D. et Kleinberg J., "Networks, Crowds, and Markets: Reasoning About a Highly Connected World" Sections 13.1 et 13.2 Accéder au site p. 7-13 Bush V., "As We May Think", juillet 1945 Accéder au site p. 15-20 Easley-Kleinberg, Section 18.7 p. 23-29 Kanade V., Levi R., Lotker Z., Mallmann-Trenn F., Mathieu C., "Distance in the Forest Fire Model: How far are you from Eve?", ACM-SIAM SODA (Symposium on Discrete Algorithms), 2016 Accéder au PDF p. 30-39 Avin C., Keller B., Lotker Z., Mathieu C., Peleg D., Pignolet Y.-A., "Homophily and the Glass Ceiling Effect in Social Networks", ITCS (Innovations in Theoretical Computer Science), 2015 Accéder au PDF p. 41 Easley-Kleinberg, Section 16.2

distance networks crowds social networks algorithmes homophily theoretical computer science mathieu c as we may think

08 - Algorithmes

Play Episode Listen Later Jan 31, 2018 53:01

Claire Mathieu Collège de France Informatique et sciences numériques (2017-2018) partenariat Inria Algorithmes Bibliographie Les numéros de pages font référence aux diapositives utilisées pour le cours. p. 4-13 et p. 22 Easley D. et Kleinberg J., "Networks, Crowds, and Markets: Reasoning About a Highly Connected World" Sections 13.1 et 13.2 Accéder au site p. 7-13 Bush V., "As We May Think", juillet 1945 Accéder au site p. 15-20 Easley-Kleinberg, Section 18.7 p. 23-29 Kanade V., Levi R., Lotker Z., Mallmann-Trenn F., Mathieu C., "Distance in the Forest Fire Model: How far are you from Eve?", ACM-SIAM SODA (Symposium on Discrete Algorithms), 2016 Accéder au PDF p. 30-39 Avin C., Keller B., Lotker Z., Mathieu C., Peleg D., Pignolet Y.-A., "Homophily and the Glass Ceiling Effect in Social Networks", ITCS (Innovations in Theoretical Computer Science), 2015 Accéder au PDF p. 41 Easley-Kleinberg, Section 16.2

distance networks crowds social networks algorithmes homophily theoretical computer science mathieu c as we may think

08 - Algorithmes - VIDEO

Play Episode Listen Later Jan 30, 2018 53:01

Claire Mathieu Collège de France Informatique et sciences numériques (2017-2018) partenariat Inria Algorithmes Bibliographie Les numéros de pages font référence aux diapositives utilisées pour le cours. p. 4-13 et p. 22 Easley D. et Kleinberg J., "Networks, Crowds, and Markets: Reasoning About a Highly Connected World" Sections 13.1 et 13.2 Accéder au site p. 7-13 Bush V., "As We May Think", juillet 1945 Accéder au site p. 15-20 Easley-Kleinberg, Section 18.7 p. 23-29 Kanade V., Levi R., Lotker Z., Mallmann-Trenn F., Mathieu C., "Distance in the Forest Fire Model: How far are you from Eve?", ACM-SIAM SODA (Symposium on Discrete Algorithms), 2016 Accéder au PDF p. 30-39 Avin C., Keller B., Lotker Z., Mathieu C., Peleg D., Pignolet Y.-A., "Homophily and the Glass Ceiling Effect in Social Networks", ITCS (Innovations in Theoretical Computer Science), 2015 Accéder au PDF p. 41 Easley-Kleinberg, Section 16.2

distance networks crowds social networks algorithmes homophily theoretical computer science mathieu c as we may think

08 - Algorithmes - PDF

Play Episode Listen Later Jan 30, 2018 53:01

Claire Mathieu Collège de France Informatique et sciences numériques (2017-2018) partenariat Inria Algorithmes Bibliographie Les numéros de pages font référence aux diapositives utilisées pour le cours. p. 4-13 et p. 22 Easley D. et Kleinberg J., "Networks, Crowds, and Markets: Reasoning About a Highly Connected World" Sections 13.1 et 13.2 Accéder au site p. 7-13 Bush V., "As We May Think", juillet 1945 Accéder au site p. 15-20 Easley-Kleinberg, Section 18.7 p. 23-29 Kanade V., Levi R., Lotker Z., Mallmann-Trenn F., Mathieu C., "Distance in the Forest Fire Model: How far are you from Eve?", ACM-SIAM SODA (Symposium on Discrete Algorithms), 2016 Accéder au PDF p. 30-39 Avin C., Keller B., Lotker Z., Mathieu C., Peleg D., Pignolet Y.-A., "Homophily and the Glass Ceiling Effect in Social Networks", ITCS (Innovations in Theoretical Computer Science), 2015 Accéder au PDF p. 41 Easley-Kleinberg, Section 16.2

distance networks crowds social networks algorithmes homophily theoretical computer science mathieu c as we may think

08 - Algorithmes

Play Episode Listen Later Jan 30, 2018 53:01

Claire Mathieu Collège de France Informatique et sciences numériques (2017-2018) partenariat Inria Algorithmes Bibliographie Les numéros de pages font référence aux diapositives utilisées pour le cours. p. 4-13 et p. 22 Easley D. et Kleinberg J., "Networks, Crowds, and Markets: Reasoning About a Highly Connected World" Sections 13.1 et 13.2 Accéder au site p. 7-13 Bush V., "As We May Think", juillet 1945 Accéder au site p. 15-20 Easley-Kleinberg, Section 18.7 p. 23-29 Kanade V., Levi R., Lotker Z., Mallmann-Trenn F., Mathieu C., "Distance in the Forest Fire Model: How far are you from Eve?", ACM-SIAM SODA (Symposium on Discrete Algorithms), 2016 Accéder au PDF p. 30-39 Avin C., Keller B., Lotker Z., Mathieu C., Peleg D., Pignolet Y.-A., "Homophily and the Glass Ceiling Effect in Social Networks", ITCS (Innovations in Theoretical Computer Science), 2015 Accéder au PDF p. 41 Easley-Kleinberg, Section 16.2

distance networks crowds social networks algorithmes homophily theoretical computer science mathieu c as we may think

08 - Algorithmes

Play Episode Listen Later Jan 30, 2018 53:01

Claire Mathieu Collège de France Informatique et sciences numériques (2017-2018) partenariat Inria Algorithmes Bibliographie Les numéros de pages font référence aux diapositives utilisées pour le cours. p. 4-13 et p. 22 Easley D. et Kleinberg J., "Networks, Crowds, and Markets: Reasoning About a Highly Connected World" Sections 13.1 et 13.2 Accéder au site p. 7-13 Bush V., "As We May Think", juillet 1945 Accéder au site p. 15-20 Easley-Kleinberg, Section 18.7 p. 23-29 Kanade V., Levi R., Lotker Z., Mallmann-Trenn F., Mathieu C., "Distance in the Forest Fire Model: How far are you from Eve?", ACM-SIAM SODA (Symposium on Discrete Algorithms), 2016 Accéder au PDF p. 30-39 Avin C., Keller B., Lotker Z., Mathieu C., Peleg D., Pignolet Y.-A., "Homophily and the Glass Ceiling Effect in Social Networks", ITCS (Innovations in Theoretical Computer Science), 2015 Accéder au PDF p. 41 Easley-Kleinberg, Section 16.2

distance networks crowds social networks algorithmes homophily theoretical computer science mathieu c as we may think

08 - Algorithmes - PDF

Play Episode Listen Later Jan 30, 2018 53:01

Claire Mathieu Collège de France Informatique et sciences numériques (2017-2018) partenariat Inria Algorithmes Bibliographie Les numéros de pages font référence aux diapositives utilisées pour le cours. p. 4-13 et p. 22 Easley D. et Kleinberg J., "Networks, Crowds, and Markets: Reasoning About a Highly Connected World" Sections 13.1 et 13.2 Accéder au site p. 7-13 Bush V., "As We May Think", juillet 1945 Accéder au site p. 15-20 Easley-Kleinberg, Section 18.7 p. 23-29 Kanade V., Levi R., Lotker Z., Mallmann-Trenn F., Mathieu C., "Distance in the Forest Fire Model: How far are you from Eve?", ACM-SIAM SODA (Symposium on Discrete Algorithms), 2016 Accéder au PDF p. 30-39 Avin C., Keller B., Lotker Z., Mathieu C., Peleg D., Pignolet Y.-A., "Homophily and the Glass Ceiling Effect in Social Networks", ITCS (Innovations in Theoretical Computer Science), 2015 Accéder au PDF p. 41 Easley-Kleinberg, Section 16.2

distance networks crowds social networks algorithmes homophily theoretical computer science mathieu c as we may think

08 - Algorithmes - VIDEO

Play Episode Listen Later Jan 30, 2018 53:01

Claire Mathieu Collège de France Informatique et sciences numériques (2017-2018) partenariat Inria Algorithmes Bibliographie Les numéros de pages font référence aux diapositives utilisées pour le cours. p. 4-13 et p. 22 Easley D. et Kleinberg J., "Networks, Crowds, and Markets: Reasoning About a Highly Connected World" Sections 13.1 et 13.2 Accéder au site p. 7-13 Bush V., "As We May Think", juillet 1945 Accéder au site p. 15-20 Easley-Kleinberg, Section 18.7 p. 23-29 Kanade V., Levi R., Lotker Z., Mallmann-Trenn F., Mathieu C., "Distance in the Forest Fire Model: How far are you from Eve?", ACM-SIAM SODA (Symposium on Discrete Algorithms), 2016 Accéder au PDF p. 30-39 Avin C., Keller B., Lotker Z., Mathieu C., Peleg D., Pignolet Y.-A., "Homophily and the Glass Ceiling Effect in Social Networks", ITCS (Innovations in Theoretical Computer Science), 2015 Accéder au PDF p. 41 Easley-Kleinberg, Section 16.2

distance networks crowds social networks algorithmes homophily theoretical computer science mathieu c as we may think

07 - Algorithmes

Play Episode Listen Later Jan 24, 2018 58:31

Claire Mathieu Collège de France Informatique et sciences numériques (2017-2018) partenariat Inria Algorithmes Bibliographie Les numéros de pages font référence aux diapositives utilisées pour le cours. p. 4-13 et p. 22 Easley D. et Kleinberg J., "Networks, Crowds, and Markets: Reasoning About a Highly Connected World" Sections 13.1 et 13.2 Accéder au site p. 7-13 Bush V., "As We May Think", juillet 1945 Accéder au site p. 15-20 Easley-Kleinberg, Section 18.7 p. 23-29 Kanade V., Levi R., Lotker Z., Mallmann-Trenn F., Mathieu C., "Distance in the Forest Fire Model: How far are you from Eve?", ACM-SIAM SODA (Symposium on Discrete Algorithms), 2016 Accéder au PDF p. 30-39 Avin C., Keller B., Lotker Z., Mathieu C., Peleg D., Pignolet Y.-A., "Homophily and the Glass Ceiling Effect in Social Networks", ITCS (Innovations in Theoretical Computer Science), 2015 Accéder au PDF p. 41 Easley-Kleinberg, Section 16.2

distance networks crowds social networks algorithmes homophily theoretical computer science mathieu c as we may think

07 - Algorithmes - VIDEO

Play Episode Listen Later Jan 24, 2018 58:31

Claire Mathieu Collège de France Informatique et sciences numériques (2017-2018) partenariat Inria Algorithmes Bibliographie Les numéros de pages font référence aux diapositives utilisées pour le cours. p. 4-13 et p. 22 Easley D. et Kleinberg J., "Networks, Crowds, and Markets: Reasoning About a Highly Connected World" Sections 13.1 et 13.2 Accéder au site p. 7-13 Bush V., "As We May Think", juillet 1945 Accéder au site p. 15-20 Easley-Kleinberg, Section 18.7 p. 23-29 Kanade V., Levi R., Lotker Z., Mallmann-Trenn F., Mathieu C., "Distance in the Forest Fire Model: How far are you from Eve?", ACM-SIAM SODA (Symposium on Discrete Algorithms), 2016 Accéder au PDF p. 30-39 Avin C., Keller B., Lotker Z., Mathieu C., Peleg D., Pignolet Y.-A., "Homophily and the Glass Ceiling Effect in Social Networks", ITCS (Innovations in Theoretical Computer Science), 2015 Accéder au PDF p. 41 Easley-Kleinberg, Section 16.2

distance networks crowds social networks algorithmes homophily theoretical computer science mathieu c as we may think

07 - Algorithmes - PDF

Play Episode Listen Later Jan 24, 2018 58:31

Claire Mathieu Collège de France Informatique et sciences numériques (2017-2018) partenariat Inria Algorithmes Bibliographie Les numéros de pages font référence aux diapositives utilisées pour le cours. p. 4-13 et p. 22 Easley D. et Kleinberg J., "Networks, Crowds, and Markets: Reasoning About a Highly Connected World" Sections 13.1 et 13.2 Accéder au site p. 7-13 Bush V., "As We May Think", juillet 1945 Accéder au site p. 15-20 Easley-Kleinberg, Section 18.7 p. 23-29 Kanade V., Levi R., Lotker Z., Mallmann-Trenn F., Mathieu C., "Distance in the Forest Fire Model: How far are you from Eve?", ACM-SIAM SODA (Symposium on Discrete Algorithms), 2016 Accéder au PDF p. 30-39 Avin C., Keller B., Lotker Z., Mathieu C., Peleg D., Pignolet Y.-A., "Homophily and the Glass Ceiling Effect in Social Networks", ITCS (Innovations in Theoretical Computer Science), 2015 Accéder au PDF p. 41 Easley-Kleinberg, Section 16.2

distance networks crowds social networks algorithmes homophily theoretical computer science mathieu c as we may think

07 - Algorithmes - VIDEO

Play Episode Listen Later Jan 23, 2018 58:31

Claire Mathieu Collège de France Informatique et sciences numériques (2017-2018) partenariat Inria Algorithmes Bibliographie Les numéros de pages font référence aux diapositives utilisées pour le cours. p. 4-13 et p. 22 Easley D. et Kleinberg J., "Networks, Crowds, and Markets: Reasoning About a Highly Connected World" Sections 13.1 et 13.2 Accéder au site p. 7-13 Bush V., "As We May Think", juillet 1945 Accéder au site p. 15-20 Easley-Kleinberg, Section 18.7 p. 23-29 Kanade V., Levi R., Lotker Z., Mallmann-Trenn F., Mathieu C., "Distance in the Forest Fire Model: How far are you from Eve?", ACM-SIAM SODA (Symposium on Discrete Algorithms), 2016 Accéder au PDF p. 30-39 Avin C., Keller B., Lotker Z., Mathieu C., Peleg D., Pignolet Y.-A., "Homophily and the Glass Ceiling Effect in Social Networks", ITCS (Innovations in Theoretical Computer Science), 2015 Accéder au PDF p. 41 Easley-Kleinberg, Section 16.2

distance networks crowds social networks algorithmes homophily theoretical computer science mathieu c as we may think

07 - Algorithmes - PDF

Play Episode Listen Later Jan 23, 2018 58:31

Claire Mathieu Collège de France Informatique et sciences numériques (2017-2018) partenariat Inria Algorithmes Bibliographie Les numéros de pages font référence aux diapositives utilisées pour le cours. p. 4-13 et p. 22 Easley D. et Kleinberg J., "Networks, Crowds, and Markets: Reasoning About a Highly Connected World" Sections 13.1 et 13.2 Accéder au site p. 7-13 Bush V., "As We May Think", juillet 1945 Accéder au site p. 15-20 Easley-Kleinberg, Section 18.7 p. 23-29 Kanade V., Levi R., Lotker Z., Mallmann-Trenn F., Mathieu C., "Distance in the Forest Fire Model: How far are you from Eve?", ACM-SIAM SODA (Symposium on Discrete Algorithms), 2016 Accéder au PDF p. 30-39 Avin C., Keller B., Lotker Z., Mathieu C., Peleg D., Pignolet Y.-A., "Homophily and the Glass Ceiling Effect in Social Networks", ITCS (Innovations in Theoretical Computer Science), 2015 Accéder au PDF p. 41 Easley-Kleinberg, Section 16.2

distance networks crowds social networks algorithmes homophily theoretical computer science mathieu c as we may think

07 - Algorithmes

Play Episode Listen Later Jan 23, 2018 58:31

Claire Mathieu Collège de France Informatique et sciences numériques (2017-2018) partenariat Inria Algorithmes Bibliographie Les numéros de pages font référence aux diapositives utilisées pour le cours. p. 4-13 et p. 22 Easley D. et Kleinberg J., "Networks, Crowds, and Markets: Reasoning About a Highly Connected World" Sections 13.1 et 13.2 Accéder au site p. 7-13 Bush V., "As We May Think", juillet 1945 Accéder au site p. 15-20 Easley-Kleinberg, Section 18.7 p. 23-29 Kanade V., Levi R., Lotker Z., Mallmann-Trenn F., Mathieu C., "Distance in the Forest Fire Model: How far are you from Eve?", ACM-SIAM SODA (Symposium on Discrete Algorithms), 2016 Accéder au PDF p. 30-39 Avin C., Keller B., Lotker Z., Mathieu C., Peleg D., Pignolet Y.-A., "Homophily and the Glass Ceiling Effect in Social Networks", ITCS (Innovations in Theoretical Computer Science), 2015 Accéder au PDF p. 41 Easley-Kleinberg, Section 16.2

distance networks crowds social networks algorithmes homophily theoretical computer science mathieu c as we may think

07 - Algorithmes - PDF

Play Episode Listen Later Jan 23, 2018 58:31

Claire Mathieu Collège de France Informatique et sciences numériques (2017-2018) partenariat Inria Algorithmes Bibliographie Les numéros de pages font référence aux diapositives utilisées pour le cours. p. 4-13 et p. 22 Easley D. et Kleinberg J., "Networks, Crowds, and Markets: Reasoning About a Highly Connected World" Sections 13.1 et 13.2 Accéder au site p. 7-13 Bush V., "As We May Think", juillet 1945 Accéder au site p. 15-20 Easley-Kleinberg, Section 18.7 p. 23-29 Kanade V., Levi R., Lotker Z., Mallmann-Trenn F., Mathieu C., "Distance in the Forest Fire Model: How far are you from Eve?", ACM-SIAM SODA (Symposium on Discrete Algorithms), 2016 Accéder au PDF p. 30-39 Avin C., Keller B., Lotker Z., Mathieu C., Peleg D., Pignolet Y.-A., "Homophily and the Glass Ceiling Effect in Social Networks", ITCS (Innovations in Theoretical Computer Science), 2015 Accéder au PDF p. 41 Easley-Kleinberg, Section 16.2

distance networks crowds social networks algorithmes homophily theoretical computer science mathieu c as we may think

07 - Algorithmes

Play Episode Listen Later Jan 23, 2018 58:31

Claire Mathieu Collège de France Informatique et sciences numériques (2017-2018) partenariat Inria Algorithmes Bibliographie Les numéros de pages font référence aux diapositives utilisées pour le cours. p. 4-13 et p. 22 Easley D. et Kleinberg J., "Networks, Crowds, and Markets: Reasoning About a Highly Connected World" Sections 13.1 et 13.2 Accéder au site p. 7-13 Bush V., "As We May Think", juillet 1945 Accéder au site p. 15-20 Easley-Kleinberg, Section 18.7 p. 23-29 Kanade V., Levi R., Lotker Z., Mallmann-Trenn F., Mathieu C., "Distance in the Forest Fire Model: How far are you from Eve?", ACM-SIAM SODA (Symposium on Discrete Algorithms), 2016 Accéder au PDF p. 30-39 Avin C., Keller B., Lotker Z., Mathieu C., Peleg D., Pignolet Y.-A., "Homophily and the Glass Ceiling Effect in Social Networks", ITCS (Innovations in Theoretical Computer Science), 2015 Accéder au PDF p. 41 Easley-Kleinberg, Section 16.2

distance networks crowds social networks algorithmes homophily theoretical computer science mathieu c as we may think

06 - Algorithmes - PDF

Play Episode Listen Later Jan 16, 2018 57:27

Claire Mathieu Collège de France Informatique et sciences numériques (2017-2018) partenariat Inria Algorithmes Bibliographie Les numéros de pages font référence aux diapositives utilisées pour le cours. p. 4-13 et p. 22 Easley D. et Kleinberg J., "Networks, Crowds, and Markets: Reasoning About a Highly Connected World" Sections 13.1 et 13.2 Accéder au site p. 7-13 Bush V., "As We May Think", juillet 1945 Accéder au site p. 15-20 Easley-Kleinberg, Section 18.7 p. 23-29 Kanade V., Levi R., Lotker Z., Mallmann-Trenn F., Mathieu C., "Distance in the Forest Fire Model: How far are you from Eve?", ACM-SIAM SODA (Symposium on Discrete Algorithms), 2016 Accéder au PDF p. 30-39 Avin C., Keller B., Lotker Z., Mathieu C., Peleg D., Pignolet Y.-A., "Homophily and the Glass Ceiling Effect in Social Networks", ITCS (Innovations in Theoretical Computer Science), 2015 Accéder au PDF p. 41 Easley-Kleinberg, Section 16.2

distance networks crowds social networks algorithmes homophily theoretical computer science mathieu c as we may think

06 - Algorithmes

Play Episode Listen Later Jan 16, 2018 57:27

Claire Mathieu Collège de France Informatique et sciences numériques (2017-2018) partenariat Inria Algorithmes Bibliographie Les numéros de pages font référence aux diapositives utilisées pour le cours. p. 4-13 et p. 22 Easley D. et Kleinberg J., "Networks, Crowds, and Markets: Reasoning About a Highly Connected World" Sections 13.1 et 13.2 Accéder au site p. 7-13 Bush V., "As We May Think", juillet 1945 Accéder au site p. 15-20 Easley-Kleinberg, Section 18.7 p. 23-29 Kanade V., Levi R., Lotker Z., Mallmann-Trenn F., Mathieu C., "Distance in the Forest Fire Model: How far are you from Eve?", ACM-SIAM SODA (Symposium on Discrete Algorithms), 2016 Accéder au PDF p. 30-39 Avin C., Keller B., Lotker Z., Mathieu C., Peleg D., Pignolet Y.-A., "Homophily and the Glass Ceiling Effect in Social Networks", ITCS (Innovations in Theoretical Computer Science), 2015 Accéder au PDF p. 41 Easley-Kleinberg, Section 16.2

distance networks crowds social networks algorithmes homophily theoretical computer science mathieu c as we may think

06 - Algorithmes - VIDEO

Play Episode Listen Later Jan 16, 2018 57:27

Claire Mathieu Collège de France Informatique et sciences numériques (2017-2018) partenariat Inria Algorithmes Bibliographie Les numéros de pages font référence aux diapositives utilisées pour le cours. p. 4-13 et p. 22 Easley D. et Kleinberg J., "Networks, Crowds, and Markets: Reasoning About a Highly Connected World" Sections 13.1 et 13.2 Accéder au site p. 7-13 Bush V., "As We May Think", juillet 1945 Accéder au site p. 15-20 Easley-Kleinberg, Section 18.7 p. 23-29 Kanade V., Levi R., Lotker Z., Mallmann-Trenn F., Mathieu C., "Distance in the Forest Fire Model: How far are you from Eve?", ACM-SIAM SODA (Symposium on Discrete Algorithms), 2016 Accéder au PDF p. 30-39 Avin C., Keller B., Lotker Z., Mathieu C., Peleg D., Pignolet Y.-A., "Homophily and the Glass Ceiling Effect in Social Networks", ITCS (Innovations in Theoretical Computer Science), 2015 Accéder au PDF p. 41 Easley-Kleinberg, Section 16.2

distance networks crowds social networks algorithmes homophily theoretical computer science mathieu c as we may think

05 - Algorithmes - VIDEO

Play Episode Listen Later Jan 9, 2018 55:29

Claire Mathieu Collège de France Informatique et sciences numériques (2017-2018) partenariat Inria Algorithmes Bibliographie Les numéros de pages font référence aux diapositives utilisées pour le cours. p. 4-13 et p. 22 Easley D. et Kleinberg J., "Networks, Crowds, and Markets: Reasoning About a Highly Connected World" Sections 13.1 et 13.2 Accéder au site p. 7-13 Bush V., "As We May Think", juillet 1945 Accéder au site p. 15-20 Easley-Kleinberg, Section 18.7 p. 23-29 Kanade V., Levi R., Lotker Z., Mallmann-Trenn F., Mathieu C., "Distance in the Forest Fire Model: How far are you from Eve?", ACM-SIAM SODA (Symposium on Discrete Algorithms), 2016 Accéder au PDF p. 30-39 Avin C., Keller B., Lotker Z., Mathieu C., Peleg D., Pignolet Y.-A., "Homophily and the Glass Ceiling Effect in Social Networks", ITCS (Innovations in Theoretical Computer Science), 2015 Accéder au PDF p. 41 Easley-Kleinberg, Section 16.2

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05 - Algorithmes

Play Episode Listen Later Jan 9, 2018 55:29

Claire Mathieu Collège de France Informatique et sciences numériques (2017-2018) partenariat Inria Algorithmes Bibliographie Les numéros de pages font référence aux diapositives utilisées pour le cours. p. 4-13 et p. 22 Easley D. et Kleinberg J., "Networks, Crowds, and Markets: Reasoning About a Highly Connected World" Sections 13.1 et 13.2 Accéder au site p. 7-13 Bush V., "As We May Think", juillet 1945 Accéder au site p. 15-20 Easley-Kleinberg, Section 18.7 p. 23-29 Kanade V., Levi R., Lotker Z., Mallmann-Trenn F., Mathieu C., "Distance in the Forest Fire Model: How far are you from Eve?", ACM-SIAM SODA (Symposium on Discrete Algorithms), 2016 Accéder au PDF p. 30-39 Avin C., Keller B., Lotker Z., Mathieu C., Peleg D., Pignolet Y.-A., "Homophily and the Glass Ceiling Effect in Social Networks", ITCS (Innovations in Theoretical Computer Science), 2015 Accéder au PDF p. 41 Easley-Kleinberg, Section 16.2

distance networks crowds social networks algorithmes homophily theoretical computer science mathieu c as we may think

05 - Algorithmes - PDF

Play Episode Listen Later Jan 9, 2018 55:29

Claire Mathieu Collège de France Informatique et sciences numériques (2017-2018) partenariat Inria Algorithmes Bibliographie Les numéros de pages font référence aux diapositives utilisées pour le cours. p. 4-13 et p. 22 Easley D. et Kleinberg J., "Networks, Crowds, and Markets: Reasoning About a Highly Connected World" Sections 13.1 et 13.2 Accéder au site p. 7-13 Bush V., "As We May Think", juillet 1945 Accéder au site p. 15-20 Easley-Kleinberg, Section 18.7 p. 23-29 Kanade V., Levi R., Lotker Z., Mallmann-Trenn F., Mathieu C., "Distance in the Forest Fire Model: How far are you from Eve?", ACM-SIAM SODA (Symposium on Discrete Algorithms), 2016 Accéder au PDF p. 30-39 Avin C., Keller B., Lotker Z., Mathieu C., Peleg D., Pignolet Y.-A., "Homophily and the Glass Ceiling Effect in Social Networks", ITCS (Innovations in Theoretical Computer Science), 2015 Accéder au PDF p. 41 Easley-Kleinberg, Section 16.2

distance networks crowds social networks algorithmes homophily theoretical computer science mathieu c as we may think

04 - Algorithmes - VIDEO

Play Episode Listen Later Dec 19, 2017 56:56

Claire Mathieu Collège de France Informatique et sciences numériques (2017-2018) partenariat Inria Algorithmes Bibliographie Les numéros de pages font référence aux diapositives utilisées pour le cours. p. 4-13 et p. 22 Easley D. et Kleinberg J., "Networks, Crowds, and Markets: Reasoning About a Highly Connected World" Sections 13.1 et 13.2 Accéder au site p. 7-13 Bush V., "As We May Think", juillet 1945 Accéder au site p. 15-20 Easley-Kleinberg, Section 18.7 p. 23-29 Kanade V., Levi R., Lotker Z., Mallmann-Trenn F., Mathieu C., "Distance in the Forest Fire Model: How far are you from Eve?", ACM-SIAM SODA (Symposium on Discrete Algorithms), 2016 Accéder au PDF p. 30-39 Avin C., Keller B., Lotker Z., Mathieu C., Peleg D., Pignolet Y.-A., "Homophily and the Glass Ceiling Effect in Social Networks", ITCS (Innovations in Theoretical Computer Science), 2015 Accéder au PDF p. 41 Easley-Kleinberg, Section 16.2

distance networks crowds social networks algorithmes homophily theoretical computer science mathieu c as we may think

04 - Algorithmes - PDF

Play Episode Listen Later Dec 19, 2017 56:56

Claire Mathieu Collège de France Informatique et sciences numériques (2017-2018) partenariat Inria Algorithmes Bibliographie Les numéros de pages font référence aux diapositives utilisées pour le cours. p. 4-13 et p. 22 Easley D. et Kleinberg J., "Networks, Crowds, and Markets: Reasoning About a Highly Connected World" Sections 13.1 et 13.2 Accéder au site p. 7-13 Bush V., "As We May Think", juillet 1945 Accéder au site p. 15-20 Easley-Kleinberg, Section 18.7 p. 23-29 Kanade V., Levi R., Lotker Z., Mallmann-Trenn F., Mathieu C., "Distance in the Forest Fire Model: How far are you from Eve?", ACM-SIAM SODA (Symposium on Discrete Algorithms), 2016 Accéder au PDF p. 30-39 Avin C., Keller B., Lotker Z., Mathieu C., Peleg D., Pignolet Y.-A., "Homophily and the Glass Ceiling Effect in Social Networks", ITCS (Innovations in Theoretical Computer Science), 2015 Accéder au PDF p. 41 Easley-Kleinberg, Section 16.2

distance networks crowds social networks algorithmes homophily theoretical computer science mathieu c as we may think

04 - Algorithmes

Play Episode Listen Later Dec 19, 2017 56:56

Claire Mathieu Collège de France Informatique et sciences numériques (2017-2018) partenariat Inria Algorithmes Bibliographie Les numéros de pages font référence aux diapositives utilisées pour le cours. p. 4-13 et p. 22 Easley D. et Kleinberg J., "Networks, Crowds, and Markets: Reasoning About a Highly Connected World" Sections 13.1 et 13.2 Accéder au site p. 7-13 Bush V., "As We May Think", juillet 1945 Accéder au site p. 15-20 Easley-Kleinberg, Section 18.7 p. 23-29 Kanade V., Levi R., Lotker Z., Mallmann-Trenn F., Mathieu C., "Distance in the Forest Fire Model: How far are you from Eve?", ACM-SIAM SODA (Symposium on Discrete Algorithms), 2016 Accéder au PDF p. 30-39 Avin C., Keller B., Lotker Z., Mathieu C., Peleg D., Pignolet Y.-A., "Homophily and the Glass Ceiling Effect in Social Networks", ITCS (Innovations in Theoretical Computer Science), 2015 Accéder au PDF p. 41 Easley-Kleinberg, Section 16.2

distance networks crowds social networks algorithmes homophily theoretical computer science mathieu c as we may think

03 - Algorithmes

Play Episode Listen Later Dec 12, 2017 56:25

Claire Mathieu Collège de France Informatique et sciences numériques (2017-2018) partenariat Inria Algorithmes Bibliographie Les numéros de pages font référence aux diapositives utilisées pour le cours. p. 4-13 et p. 22 Easley D. et Kleinberg J., "Networks, Crowds, and Markets: Reasoning About a Highly Connected World" Sections 13.1 et 13.2 Accéder au site p. 7-13 Bush V., "As We May Think", juillet 1945 Accéder au site p. 15-20 Easley-Kleinberg, Section 18.7 p. 23-29 Kanade V., Levi R., Lotker Z., Mallmann-Trenn F., Mathieu C., "Distance in the Forest Fire Model: How far are you from Eve?", ACM-SIAM SODA (Symposium on Discrete Algorithms), 2016 Accéder au PDF p. 30-39 Avin C., Keller B., Lotker Z., Mathieu C., Peleg D., Pignolet Y.-A., "Homophily and the Glass Ceiling Effect in Social Networks", ITCS (Innovations in Theoretical Computer Science), 2015 Accéder au PDF p. 41 Easley-Kleinberg, Section 16.2

distance networks crowds social networks algorithmes homophily theoretical computer science mathieu c as we may think

03 - Algorithmes - PDF

Play Episode Listen Later Dec 12, 2017 56:25

Claire Mathieu Collège de France Informatique et sciences numériques (2017-2018) partenariat Inria Algorithmes Bibliographie Les numéros de pages font référence aux diapositives utilisées pour le cours. p. 4-13 et p. 22 Easley D. et Kleinberg J., "Networks, Crowds, and Markets: Reasoning About a Highly Connected World" Sections 13.1 et 13.2 Accéder au site p. 7-13 Bush V., "As We May Think", juillet 1945 Accéder au site p. 15-20 Easley-Kleinberg, Section 18.7 p. 23-29 Kanade V., Levi R., Lotker Z., Mallmann-Trenn F., Mathieu C., "Distance in the Forest Fire Model: How far are you from Eve?", ACM-SIAM SODA (Symposium on Discrete Algorithms), 2016 Accéder au PDF p. 30-39 Avin C., Keller B., Lotker Z., Mathieu C., Peleg D., Pignolet Y.-A., "Homophily and the Glass Ceiling Effect in Social Networks", ITCS (Innovations in Theoretical Computer Science), 2015 Accéder au PDF p. 41 Easley-Kleinberg, Section 16.2

distance networks crowds social networks algorithmes homophily theoretical computer science mathieu c as we may think

03 - Algorithmes - VIDEO

Play Episode Listen Later Dec 12, 2017 56:25

Claire Mathieu Collège de France Informatique et sciences numériques (2017-2018) partenariat Inria Algorithmes Bibliographie Les numéros de pages font référence aux diapositives utilisées pour le cours. p. 4-13 et p. 22 Easley D. et Kleinberg J., "Networks, Crowds, and Markets: Reasoning About a Highly Connected World" Sections 13.1 et 13.2 Accéder au site p. 7-13 Bush V., "As We May Think", juillet 1945 Accéder au site p. 15-20 Easley-Kleinberg, Section 18.7 p. 23-29 Kanade V., Levi R., Lotker Z., Mallmann-Trenn F., Mathieu C., "Distance in the Forest Fire Model: How far are you from Eve?", ACM-SIAM SODA (Symposium on Discrete Algorithms), 2016 Accéder au PDF p. 30-39 Avin C., Keller B., Lotker Z., Mathieu C., Peleg D., Pignolet Y.-A., "Homophily and the Glass Ceiling Effect in Social Networks", ITCS (Innovations in Theoretical Computer Science), 2015 Accéder au PDF p. 41 Easley-Kleinberg, Section 16.2

distance networks crowds social networks algorithmes homophily theoretical computer science mathieu c as we may think

02 - Algorithmes

Play Episode Listen Later Dec 5, 2017 51:07

Claire Mathieu Collège de France Informatique et sciences numériques (2017-2018) partenariat Inria Algorithmes Bibliographie Les numéros de pages font référence aux diapositives utilisées pour le cours. p. 4-13 et p. 22 Easley D. et Kleinberg J., "Networks, Crowds, and Markets: Reasoning About a Highly Connected World" Sections 13.1 et 13.2 Accéder au site p. 7-13 Bush V., "As We May Think", juillet 1945 Accéder au site p. 15-20 Easley-Kleinberg, Section 18.7 p. 23-29 Kanade V., Levi R., Lotker Z., Mallmann-Trenn F., Mathieu C., "Distance in the Forest Fire Model: How far are you from Eve?", ACM-SIAM SODA (Symposium on Discrete Algorithms), 2016 Accéder au PDF p. 30-39 Avin C., Keller B., Lotker Z., Mathieu C., Peleg D., Pignolet Y.-A., "Homophily and the Glass Ceiling Effect in Social Networks", ITCS (Innovations in Theoretical Computer Science), 2015 Accéder au PDF p. 41 Easley-Kleinberg, Section 16.2

distance networks crowds social networks algorithmes homophily theoretical computer science mathieu c as we may think

02 - Algorithmes - PDF

Play Episode Listen Later Dec 5, 2017 51:07

Claire Mathieu Collège de France Informatique et sciences numériques (2017-2018) partenariat Inria Algorithmes Bibliographie Les numéros de pages font référence aux diapositives utilisées pour le cours. p. 4-13 et p. 22 Easley D. et Kleinberg J., "Networks, Crowds, and Markets: Reasoning About a Highly Connected World" Sections 13.1 et 13.2 Accéder au site p. 7-13 Bush V., "As We May Think", juillet 1945 Accéder au site p. 15-20 Easley-Kleinberg, Section 18.7 p. 23-29 Kanade V., Levi R., Lotker Z., Mallmann-Trenn F., Mathieu C., "Distance in the Forest Fire Model: How far are you from Eve?", ACM-SIAM SODA (Symposium on Discrete Algorithms), 2016 Accéder au PDF p. 30-39 Avin C., Keller B., Lotker Z., Mathieu C., Peleg D., Pignolet Y.-A., "Homophily and the Glass Ceiling Effect in Social Networks", ITCS (Innovations in Theoretical Computer Science), 2015 Accéder au PDF p. 41 Easley-Kleinberg, Section 16.2

distance networks crowds social networks algorithmes homophily theoretical computer science mathieu c as we may think

02 - Algorithmes - VIDEO