As a style, the “award acceptance lecture” is little greater than a formality and a banality. However there may be not less than one charming exception to this rule—the talks given by the foremost laptop scientists on the event of their Turing Awards.
Some learn like manifestos: John Backus’ “Can Programming Be Liberated From the von Neumann Style?” (1977) impressed a brand new paradigm that begat purposeful languages like Haskell. Others are warnings: In his “Reflections on Trusting Trust” (1984), Ken Thompson demonstrated the peril of backdoored compilers, seemingly stopping scads of safety vulnerabilities. Edsger Dijkstra, in “The Humble Programmer” (1972), urged his ilk to be cautious of cleverness and acknowledge “the intrinsic limitations of the human thoughts.”
For our functions, think about Kenneth Iverson’s heady 1979 lecture, “Notation as a Tool of Thought.” In it, he demonstrated that mathematical notations aren’t simply handy shorthand—CO2 for carbon dioxide, 3,888 for MMMDCCCLXXXVIII—in addition they make new insights readily discoverable. Because the mathematician Alfred North Whitehead as soon as put it: “By relieving the mind of all pointless work, a very good notation units it free to focus on extra superior issues.”
Iverson gained his Turing Award for APL, a spooky-looking programming language that started its life as a system of notation for bridging between languages. Within the early days of scientific computing, programmers needed to assume in a single language (mathematical notation) however then program in one other (e.g., Fortran). APL was designed in order that unwieldy operations may very well be written as compactly as equations—strains of code collapsed into a few symbols like + or ×. APL turned out to be extra influential than adopted, however regardless of: It confirmed that two languages may very well be fused into one.
The 12 months 2026 marks 60 years for the reason that introduction of APL, and a brand new sort of two-language drawback bedevils the sector of scientific computing. The ruling programming language is Python, nevertheless it reigns not as a muscular conqueror a lot as a doddering king. Python, in different phrases, is very sluggish—a flaw that even its most ardent defenders wouldn’t deny.
Therefore the two-language drawback: Researchers prototype in sluggish, pleasant Python however, for performance-critical components, rewrite in quicker, much less pleasant languages like C++ or Rust. This limitation can’t be solved by spinning up a platoon of AI coding brokers, as a result of regardless of how a lot you optimize a sluggish language, a quicker one will outperform it.
These binary trade-offs exist in different domains. You may say that development, as an illustration, has a two-material drawback. Wooden is a pliable materials for prototyping a construction—even an novice can noticed and nail collectively a purposeful constructing. Nevertheless it’s no good for erecting a skyscraper. This raises an apparent query: What if there have been a cloth as manipulable as wooden however as robust as metal? What if there have been a language as ergonomic as Python however as quick as C?
In 2012, 4 laptop scientists with robust mathematical bona fides got here collectively to handle the modern-day two-language drawback. In a brief essay referred to as “Why We Created Julia,” they mentioned they took up the venture “as a result of we’re grasping.” Their textual content begins like a valentine to programming languages:
We’re energy Matlab customers. A few of us are Lisp hackers. Some are Pythonistas, others Rubyists, nonetheless others Perl hackers … We’ve generated extra R plots than any sane individual ought to. C is our desert island programming language.
However each one in every of these languages, they wrote, “is ideal for some elements of the work and horrible for others.” Grasping as they have been, they wished “a language that’s open supply, with a liberal license … One thing that’s grime easy to study, but retains probably the most critical hackers pleased.” Julia could be the one language to unite all of them.
