LISP, an acronym for list processing, is a programming language that was designed for easy manipulation of data strings. It is a commonly used language for artificial intelligence (AI) programming.
LISP, an acronym for list processing, is a programming language that was designed for easy manipulation of data strings. It is a commonly used language for artificial intelligence (AI) programming.
Invented by John McCarthy (1958)
Two simple data structure (atoms and lists)
Heavy use of recursion
Interpretive language
Variations
Scheme
Common Lisp (de facto industrial standard)
Most widely used AI programming language
Functional Programming Paradigm
Low maintenance overhead
LISP Language, LISP Introduction, List Processing, LISP Syntax, Lisp Comparison Structures, Lisp Applications. Using of LISP language in Artificial Intelligence
Presentation introducing LISP, looking at the history and concepts behind this powerfull programming language.
Presentation by Tijs van der Storm for the sept 2012 Devnology meetup at the Mirabeau offices in Amsterdam
Invented by John McCarthy (1958)
Two simple data structure (atoms and lists)
Heavy use of recursion
Interpretive language
Variations
Scheme
Common Lisp (de facto industrial standard)
Most widely used AI programming language
Functional Programming Paradigm
Low maintenance overhead
LISP Language, LISP Introduction, List Processing, LISP Syntax, Lisp Comparison Structures, Lisp Applications. Using of LISP language in Artificial Intelligence
Presentation introducing LISP, looking at the history and concepts behind this powerfull programming language.
Presentation by Tijs van der Storm for the sept 2012 Devnology meetup at the Mirabeau offices in Amsterdam
A story about JavaScript History and its future. I'm talking about language design, ECMA standards, JavaScript code generation, and Virtual Machines made on JS.
A public beta version of Windows 10 branded as Windows Technical Preview (later known as Windows Insider Preview) was released on October 1, 2014. Windows 7, Windows Vista, Windows 8 and Windows 8.1 are able to upgrade into Windows 10 and also able to roll back into previous OS if you want.
Windows 10 won’t be launching for quite a while but we already know a lot about Microsoft’s upcoming OS. From Xbox for Windows and Cortana for desktop to a resurrected Start Menu and new multitasking tools, the new platform will offer a bevy of new features. These are the 10 best.
JavaScript and popular programming paradigms (OOP, AOP, FP, DSL). Overview of the language to see what tools we can leverage to reduce complexity of our projects.
This part goes over more language features and looks at FP, and DSLs with JavaScript.
The presentation was delivered at ClubAJAX on 3/2/2010.
Blog post: http://lazutkin.com/blog/2010/mar/4/exciting-js-2/
Beginning is Part I: http://www.slideshare.net/elazutkin/exciting-javascript-part-i
Key lecture for the EURO-BASIN Training Workshop on Introduction to Statistical Modelling for Habitat Model Development, 26-28 Oct, AZTI-Tecnalia, Pasaia, Spain (www.euro-basin.eu)
C is a general-purpose high level language that was originally developed by Dennis Ritchie for the Unix operating system. It was first implemented on the Digital Equipment Corporation PDP-11 computer in 1972.
An introduction to the basic concepts on functional programming, explaining why it is a hot topic for some years now, what it is and some suggestions of functional languages to be learned.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
2. What is Scheme?
• Scheme is a dialect of Lisp, around since the
70s
• Functional, although not “pure”
• Extremely minimal, concise, and expressive
• Fully defined in R5RS [1]
• Build bigger parts from smaller parts
λ
3. Implementations
• Scheme by itself is the language specification
• There are many implementations of
Scheme, each with different strengths:
• Gambit-C: speed, portability
• PLT: ease-of-use, libraries
• Scheme48: modules, formal semantics
• etc.
λ
6. Functions
• `define` declares functions
• (define (multiply x y)
(other-function x)
(* x y))
• The last value is returned, so unless
`other-function` has a side effect, that call
is essentially ignored
• `define` also create variables
• (define foo 5)
λ
7. Functions
• `lambda` creates an anonymous function
• (lambda () (+ 1 2))
• (lambda (x y) (* x y))
• lambdas are ubiquitous in Scheme, too
powerful to fully explain here, but it’s
another dimension of Scheme’s
expressiveness
• Our “multiply” function could be defined as:
• (define multiply (lambda (x y) (* x y))) λ
8. Functions
• Functions are full closures with tail-
recursion where possible
• (define (foo x y)
(define z (get-z-axis))
(lambda () (+ x y z)))
• (define (bar)
(read-network-blocking-and-act)
(bar))
λ
9. Identifiers
• The name of an identifier is very flexible; can
contain almost any character
• Very expressive
• (define the-number 5)
• (define !@#$%^&* 10)
• (define (is-alive?) ...)
λ
10. Lists
• The list is Scheme’s fundamental data
structure
• Special syntax for lists:
• ‘(1 2 3 “foo”)
• ‘(1 2 3 (4 5 6))
• `(1 2 3 ,data) (define data “foo”)
• `(1 2 3 ,@data) (define data ‘(4 5 6))
λ
11. Lists
• Lists are made up of “cons cells” or pairs
• Fundamental list functions:
• car
• (car ‘(1 2 3)) => 1
• cdr
• (cdr ‘(1 2 3)) => (2 3)
• cons
• (cons 1 ‘(2 3)) => (1 2 3) λ
12. Lists
• Question: is a function not simply a list of
elements?
• ‘(define (foo x y) (* x y))
• Yes, it is.
• In fact, any code in Scheme is data — simply
a list of elements.
λ
13. Macros
• Macros are Scheme functions that take
arguments and expand into different code
• Macros usually parse code, which is easy in
Scheme because code is data!
• (define-macro (my-define func . body)
(let ((name (car func))
(args (cdr func)))
`(define ,name (lambda ,args ,@body))))
• (my-define (foo x y) (* x y)) expands into
• (define foo (lambda (x y) (* x y))) λ
14. Macros
• Macros are lazy
• Macros allow an extremely powerful tool for
extending the language for your needs
• Any new construct can be integrated
• You could redefine `if`
• Other macro systems exist which integrate
pattern matching and other features
λ
15. Say again?
• Because of consistency and conciseness, it’s
easy to write reusable, small bits of code in
Scheme, which is good
• Other libraries implement tons of stuff, such
as object systems, vectors, etc.
• SRFI’s
• Not covered: continuations, eval, and more
• Questions or comments?
λ
16. Practical Examples
• It turns out that it’s easy to implement
functional programming in an imperative
language like C [3]
• Gambit-C is a Scheme system which takes
Scheme and compiles it to C [2]
• Extremely fast and portable
• Easy to interface to C/C++/Obj-C
libraries
λ
17. Taking Scheme to the iPhone
• Cross-compiled Gambit’s run-time library
for the ARM architecture (for the iPhone)
• Compiled my Scheme code to C
• Linked everything together, and it ran fine!
• Wasn’t that easy? [4]
λ
19. Benefits
• Write iPhone apps in Scheme, of course
• Garbage collector
• Faster, real-time development
• Load in Scheme files at run-time
• Much more sane debugging
λ
20. Loading in Scheme at run-time
• Scheme has a `load` procedure which takes
a filename, loads in the code and evaluates it
• In Gambit, this function loads code at run-
time (`include` does the same thing at
compile-time)
• Compile an app with a `load` statement,
install it once, and develop with interpreted
code forever.
λ
22. Sane Debugging
• What is a REPL?
• Read-Eval-Print-Loop
• A debugger is a REPL with special
commands
• Gambit comes with a nice command-line
debugger, so we want this to work for our
iPhone apps.
λ
23. Sane Debugging
• Since code is simply S-expressions, it’s really
easy to parse, pass around the network, etc.
• We’ve created a “remote debugger” which
implements the functionality of a networked
REPL
• Instead of reading from the console, the
REPL reads and writes from/to a network
port
• A “debugging server” gives you access to
REPLs running inside the application λ
25. Optimizing
• Compiling to C makes it easy to fine tune
hotspots in your application
• (define fast-sqrt
(c-lambda (float) float “fast_sqrt”))
• Once you’ve written and debugged your app
sanely, profile and optimize specific parts of
your app
• Re-write small pieces of code in C
• Use `declare` in Gambit λ
26. Paredit
• Another benefit of concise syntax is more
advanced text editing
• Instead of thinking in terms of lines, think in
terms of S-expressions
• Paredit implements key-bindings in Emacs to
manipulate S-expressions
• Really powerful way of writing code
λ