#coq software

[scrsoft]

What is an APQP Checklist?

An Advanced Product Quality Planning (APQP) checklist is a vital tool used in various industries to ensure the systematic development of products and processes. It serves as a comprehensive guide to managing quality throughout the product lifecycle, from initial design to production and beyond.

Importance of APQP in Quality Management

APQP plays a crucial role in maintaining product quality and customer satisfaction. By following a structured approach outlined in the checklist, organizations can:

Ensure Product Quality: APQP helps in identifying potential risks and quality issues early in the product development stage, allowing for timely mitigation measures.

Reduce Defects and Rework: Through thorough planning and risk assessment, APQP aims to minimize defects and rework, thereby reducing overall production costs.

Understanding the APQP Checklist

An APQP checklist is a document that outlines the necessary steps and requirements for implementing APQP processes effectively. It typically includes:

Definition: A clear definition of APQP and its objectives.

Components of the Checklist: Sections covering various aspects such as planning, design, process validation, and production.

Benefits of Using an APQP Checklist

The utilization of an APQP checklist offers several benefits, including:

Streamlining Processes: By following a structured approach, organizations can streamline their product development and manufacturing processes.

Enhancing Communication: The checklist facilitates effective communication among cross-functional teams, ensuring everyone is aligned with project requirements.

Facilitating Risk Management: APQP checklist helps in identifying and mitigating risks early in the product lifecycle, reducing the likelihood of costly failures.

How to Develop an Effective APQP Checklist

Developing an effective APQP checklist involves several key steps:

Gathering Relevant Information: Collecting necessary data and information related to product requirements, customer expectations, and regulatory standards.

Involving Cross-Functional Teams: Engaging representatives from various departments to ensure comprehensive input and buy-in.

Establishing Clear Criteria and Metrics: Defining specific criteria and metrics for evaluating product quality and process performance.

Implementing the APQP Checklist in Different Industries

APQP principles can be applied across various industries, including:

Automotive Sector: APQP is widely used in the automotive industry to ensure the quality and safety of vehicles.

Aerospace Industry: Aerospace companies utilize APQP to meet stringent regulatory requirements and ensure the reliability of aircraft components.

Healthcare Sector: In healthcare, APQP helps in developing safe and effective medical devices and pharmaceutical products.

Common Mistakes to Avoid When Using APQP Checklist

While APQP checklist offers numerous benefits, organizations must avoid common pitfalls such as:

Lack of Stakeholder Involvement: Failure to involve key stakeholders from different departments can lead to oversight and suboptimal outcomes.

Failure to Update the Checklist Regularly: An outdated checklist may not reflect current industry standards or regulatory requirements, compromising its effectiveness.

Ignoring Feedback and Improvement Opportunities: Organizations should actively seek feedback from users and stakeholders to identify areas for improvement and refinement.

Examples of APQP Checklist Templates

There are various APQP checklist templates available, ranging from basic to advanced, tailored to specific industry requirements.

Basic Checklist Template: Includes essential steps and requirements for implementing APQP processes.

Advanced Checklist Template: Incorporates additional features such as risk assessment matrices and validation protocols.

Tips for Maximizing the Effectiveness of APQP Checklist

To derive maximum benefit from APQP checklist, organizations should:

Provide Adequate Training: Ensure that employees are trained in APQP principles and understand how to use the checklist effectively.

Regular Audits and Reviews: Conduct periodic audits and reviews to assess compliance with APQP processes and identify areas for improvement.

Continuous Improvement Initiatives: Encourage a culture of continuous improvement, where feedback is solicited, and lessons learned are applied to enhance processes.

Case Studies: Successful Implementation of APQP Checklist

Several organizations have successfully implemented APQP checklist, resulting in improved product quality and customer satisfaction.

Future Trends in APQP Checklist Development

As technology advances and industry requirements evolve, APQP checklist development is expected to incorporate:

Integration with Digital Tools: Increasing integration with digital tools and software platforms to streamline APQP processes and enhance collaboration.

Emphasis on Sustainability: Incorporating sustainability criteria and metrics into APQP checklist to address growing environmental concerns.

Conclusion

In conclusion, an APQP checklist is a valuable tool for organizations seeking to ensure product quality, minimize risks, and enhance customer satisfaction. By following a structured approach outlined in the checklist, businesses can streamline their product development processes and stay competitive in today's dynamic market.

FAQs

What is the role of APQP in quality management?

APQP plays a crucial role in maintaining product quality by identifying potential risks and quality issues early in the product development stage.

How can organizations develop an effective APQP checklist?

Developing an effective APQP checklist involves steps such as gathering relevant information, involving cross-functional teams, and establishing clear criteria and metrics.

In which industries is APQP commonly used?

APQP principles can be applied across various industries, including automotive, aerospace, and healthcare sectors.

What are some common mistakes to avoid when using an APQP checklist?

Common mistakes include lack of stakeholder involvement, failure to update the checklist regularly, and ignoring feedback and improvement opportunities.

How can organizations maximize the effectiveness of APQP checklist?

Organizations can maximize effectiveness by providing adequate training, conducting regular audits and reviews, and fostering a culture of continuous improvement.

[digitalsfontssoccer]

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[robotabc773]

math asks! 18, 19, 23, 40, 56, 59 (or ofc some subset, like you said)

18+19: Can you share a good math problem you’ve solved recently? How did you solve it?

I was recently several tangents down a research rabbit hole and discovered that CC: Tweaked (the modern fork of the minecraft mod ComputerCraft), instead of allowing its computers to simply know where they are in the world, instead has a built-in gps library that works on top of the rednet networking system which is itself built on top of the built-in support for wireless modems to communicate between computers. It works because sending messages via modem tells you the distance between the two communicating computers, so with a set of 4 computers that all know their own locations and are setup in the right configuration, any other computer can talk to them and trilaterate its position. Which then of course got me thinking about the amount of information you gain from knowing your distance to a particular number of fixed points and how that generalizes to multiple dimensions. I believe what we get is both our position as projected onto the space spanned by the fixed points as well as our distance to that space. I don't have an actual proof for this but I'd love to know if anyone has one or knows the name of this concept so that I can look one up!

23: Will P=NP? Why or why not?

Well for the sake of cryptography working I really hope that P≠NP because otherwise we're kinda screwed on that front. Intuitively it seems like that should be the case, like I'd expect that there should be some problems that are hard to solve even if they're easy to check.

40. What’s the silliest Mathematical mistake you’ve ever made?

I really wish I had a good story to tell here but I can't think of one sorry :c

56. Do you have a favorite sequence? Is it in the OEIS?

I often find myself with favorites in considerably less categories than I am asked about. This is one such case.

59. Can you recommend any online resources for math?

Ooh this is a little sideways from what I'd normally think of as just math (in the direction of CS of course), but I'd highly recommend The Natural Number Game, an interactive introduction to formalized proofs in Lean! If you enjoy it, Software Foundations is a great (and free!) series of textbooks to learn how to apply these techniques to the task of formalizing and proving properties of programming languages (using a similar but separate language called Coq)

[argumate]

Suppose we condition on the assumption “AI based x-risk is worth spending some money on avoiding.”. If some money for that was, as I think you suggested, to be put towards “software safety” techniques, what more specific approaches/projects to further “software safety” do you think would be most effective at reducing AI based x-risk ? (This might be effectively the same question as “What do you think would be most effective for advancing software safety?”, idk.) Would it be like, funding LEAN development, or maybe stuff with Agda or Coq or Isabelle? Or something else? Maybe researching better ways to write formal specs? Or better testing methodologies?

yes all that, but also shifting incentives in favour of using the tools and techniques that we already have, whether through regulatory means or by hunting down C++ programmers in the street like animals etc.

[ravelite]

Today, the team declared victory. They’ve finally verified the true value of a number called BB(5), which quantifies just how busy that fifth beaver is. They obtained the result — 47,176,870 — using a piece of software called the Coq proof assistant, which certifies that mathematical proofs are free of errors.

Amateur Mathematicians Find Fifth ‘Busy Beaver’ Turing Machine | Quanta Magazine

[theohonohan]

A not-so-bitter lesson

The Bitter Lesson is an essay that makes the claim that, in AI, computational brute force tends to sweep before it. As hardware gets faster, old attempts to model cognition are in danger of being made irrelevant, no matter how elegant or promising they once seemed.

A more general principle is the idea that computer science is not governed by ideas, but by what can be done on the available hardware. Computer scientists would like to think that ideas are what matter, rather than whatever hardware is currently on the shelves. In the field of Programming Language Theory, in particular, there is a focus on “ideas of lasting value”, as opposed to incidental technical details which will inevitably quickly become obsolete. It’s valid to aim to teach undergraduates only material of lasting value—but there’s also an element of prestige attached to the supposedly eternal truths the academics are working on. When Robert Harper refers to the fact that the mathematical idea of a variable (as used in functional programming languages) has been around since “antiquity”, it’s clear that he intends this to be evidence for its canonical importance. For some, the Greek letters and apparent impenetrability of PLT seem to be evidence of elitism. There’s also, perhaps, an element of insecurity. The Curry-Howard correspondence is most often used by computer scientists to borrow ideas from the more august, tweedy and established discipline of logic (rather than allowing logic to borrow from computing). It’s an isomorphism, but in practice it has a direction: from logic to functional programming.

Most undergraduates realise that coming up with elegant concepts is just building castles in the sky until their effectiveness is mathematically proven or measured in practice. Every student learns this not-so-bitter lesson: that you can’t just invent grand and clever-sounding computer science concepts in a vacuum. They learn that intricate algorithms, with good asymptotic performance, are often bested by brute force approaches, due to the complexity of real machines and compilers. Knowing this, they don’t get attached to their ingenious ideas when they turn out not to be an improvement on more obvious or established methods.

I’m an observer of the Haskell (and Agda, Coq, etc.) scene, and it seems to me that it suffers from this problem of overvaluing elegant ideas. The Haskell community will tell you that they are pursuing truly important, timeless principles of programming, rooted in category theory. Well, they won’t tell you that, but it’s implicit that they are pursuing “ideas of lasting value” rather than working pragmatically (and straightforwardly) with the latest hardware. There are plenty of valuable concepts in the Haskell canon, but there are also ways in which Haskell is disconnected from the kind of software than 99% of the world needs to write. In my opinion, the lack of a repertoire of Haskell patterns for solving typical problems is evidence of this. With Haskell, the correct approach seems to be that the programmer should be a mathematician, should think very hard and come up with an exotic abstraction that is applicable to the problem, and should then write their program from scratch, guided by pure intuition (and, I suppose, using a few Haskell libraries). Haskell is the opposite of a glue language: Haskell is for solving problems with your intellect rather than solving them by downloading and combining packages which other people have put together. This orientation towards difficulty and abstraction is prestigious, but it’s not always appropriate—perhaps not even often appropriate. Looking for a quick, dumb solution (“worse is better”) is a much lower-maintenance strategy.

The not-so-bitter lesson is that it is the running code that matters, not the (possibly gratifying) thought and problem-solving that led to it. The code is the proof, but, unlike proofs in mathematics, it may be invalidated by changes in technology. Mathematical proofs have a kind of monotonicity: a proof, once established, can never be rolled back by being disproved—only by being forgotten. These demonstrations, these temporary, contingent proofs of the effectiveness of the programmer’s thinking seem to me to be what matters. Computer science would be very different without hardware.

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[catscomputerscreativewriting]

Oh great, they made a game about my life.

Anyway, if you find that Lean isn't quite your thing, you can go through the first book of Software Foundations. It's actually written in language of the proof assistant it teaches you! The textbook itself is executable code! And because it's written in a proof assistant (hand-waving here but don't worry about it), it's also a correct proof!!!

Ah, but then we have a problem. The name of the proof assistant.

You see, it was co-developed by one Thierry Coquand, a big deal mathematician and computer scientist.

And they named this proof assistant after him, at least that's part of the reason it has the name it has! It's also a French word for a cute animal.

...

They called it "Coq." :(

Mathematics people interested in either learning about the Peano axioms of natural numbers (how do you prove a+b = b+a) or interested in learning a proving assistant (Lean) should DEFINITELY check out the natural number game. This is a game which teaches you both of these things step by step, and has you construct the natural numbers and their most important properties from the very basic axioms. Even if you just like logical puzzles and are interested in a bit of mathematics you should check it out!

[the-blockchain-news]

Tezos Foundation Backs Blockchain Research by Inria and Tarides

Tezos Foundation Backs Blockchain Research by Inria and Tarides

The Tezos Foundation today announced two fresh partnerships to encourage the development of technologies underlying the Tezos protocol. Tezos will be backing the French National Institute for computer science and applied mathematics, Inria, and development company Tarides, also based in France.

The Foundation said, in a statement: “The Tezos Foundation is committed to funding relevant research…

[lovelanguageisolate]

I'm actually kind of spooked by machine learning. Mostly in a good way.

I asked ChatGPT to translate the Christoffel symbols (mathematical structures from differential geometry used in general relativity to describe how metrics change under parallel transport, which I've been trying to grok) into Coq.

And the code it wrote wasn't correct.

But!

It unpacked the mathematical definitions, mapping them pretty faithfully into Coq in a few seconds, explaining what it was doing lucidly along the way.

It used a bunch of libraries for real analysis, algebra, topology that have maybe been read by a few dozen people combined at a couple of research labs in France and Washington state. It used these, sometimes combining code fragments in ways that didn't type check, but generally in a way that felt idiomatic.

Sometimes it would forget to open modules or use imported syntax. But it knew the syntax it wanted! It decided to Yoneda embed a Riemannian manifold as a kind of real-valued presheaf, which is a very promising strategy. It just...mysteriously forgot to make it real-valued.

Sometimes it would use brackets to index into vectors, which is never done in Coq. But it knew what it was trying to compute!

Sometimes it would pass a tactic along to a proof obligation that the tactic couldn't actually discharge. But it knew how to use the conduit pattern and thread proof automation into definitions to deal with gnarly dependent types! This is really advanced Coq usage. You won't learn it in any undergraduate classes introducing computer proof assistants.

When I pointed out a mistake, or a type error, it would proffer an explanation and try to fix it. It mostly didn't succeed in fixing it, but it mostly did succeed in identifying what had gone wrong.

The mistakes it made had a stupid quality to them. At the same time, in another way, I felt decisively trounced.

Writing Coq is, along some hard-to-characterize verbal axis, the most cognitively demanding programming work I have done. And the kinds of assurance I can give myself about what I write when it typechecks are in a totally different league from my day job software engineering work.

And ChatGPT mastered some important aspects of this art much more thoroughly than I have after years of on-and-off study—especially knowing where to look for related work, how to strategize about building and encoding things—just by scanning a bunch of source code and textbooks. It had a style of a broken-in postdoc, but one somehow familiar with every lab's contributions.

I'm slightly injured, and mostly delighted, that some vital piece of my comparative advantage has been pulled out from under me so suddenly by a computer.

What an astounding cognitive prosthesis this would be if we could just tighten the feedback loops and widen the bandwidth between man and machine. Someday soon, people will do intellectual work the way they move about—that is, with the aid of machines that completely change the game. It will render entire tranches of human difference in ability minute by comparison.

[youzicha]

☕️: computer algebra systems

I haven't really used computer algebra systems myself, but I do have a related take, which is how poorly this technology has penetrated into the theorem proving world.

As I see it there's (at least) three different classes of software which could be called mechanized theorem proving, with progressively greater levels of formality:

Computer algebra like Mathematica. You want to know if a given inequality over real numbers is true, so you type it into the command line and the computer says "yes", by running some algorithm.

Automatic theorem provers like SMT solvers; they try to derive a proof in (typically) first-order logic, and call out to various algorithms to decide statements about (e.g.) inequalities over reals.

Proof systems with a small logical kernel, like Coq, Lean, Isabelle/HOL, etc. They build up a proof in (e.g.) first-order logic, and every step of the proof is done by inferences from a small set of axioms about (e.g.) real numbers.

Unfortunately, the decision procedures available for (2-3) are much weaker than what the computer algebra systems can do. They can handle linear things, but as soon as you have some multiplications in your formula it all breaks down.

This came up for some project I was working on: as part of it we wanted to prove some inequality, and you could see that it's true by just pasting it into Wolfram Alpha, but unfortunately we then still needed to do a complicated set of algebraic manipulations to convince the computer...

I guess this is partly a social problem (the proof assistant people and the computer algebra people are mostly disjoint), and partly a software engineering problem (they are disjoint because each of them gather around some particular legacy software with hundreds of thousands of lines of code going back to the 1980s).

I really like the idea of formal verification, but you can keenly feel the gap between the potential of the idea and the current state of the art. On one hand I'd like to hole up in an Anathem-style concent for a century to see how it goes; on the other hand I wonder if all of these decades of work will be instantly obsolete as soon as anyone bothers to put a few GPUs on it.

[tastydregs]

The Effort to Build the Mathematical Library of the Future

“Two years ago you would have had to [apply the associative property] yourself in Lean,” said Amelia Livingston, an undergraduate math major at Imperial College London who is learning Lean from Buzzard. “Then [someone] wrote a tactic that can do it all for you. Every time I use it, I get very happy.”

Altogether, it took Morrison 20 minutes to complete Euclid’s proof. In some places he filled in the details himself; in others he used tactics to do it for him. At each step, Lean checked to make sure his work was consistent with the program’s underlying logical rules, which are written in a formal language called dependent type theory.

“It’s like a sudoku app. If you make a move that’s not valid, it will go buzz,” Buzzard said. At the end, Lean certified that Morrison’s proof worked.

The exercise was exciting in the way it always is when technology steps in to do something you used to do yourself. But Euclid’s proof has been around for more than 2,000 years. The kinds of problems mathematicians care about today are so complicated that Lean can’t even understand the questions yet, let alone support the process of answering them.

“It will likely be decades before this is a research tool,” said Heather Macbeth of Fordham University, a fellow Lean user.

So before mathematicians can work with Lean on the problems they really care about, they have to equip the program with more mathematics. That’s actually a relatively straightforward task.

“Lean being able to understand something is pretty much just a matter of human beings having [translated math textbooks] into the form Lean can understand,” Morrison said.

Unfortunately, straightforward doesn’t mean easy, especially considering that for a lot of mathematics, textbooks don’t really exist.

Scattered Knowledge

If you didn’t study higher math, the subject probably seems exact and well-documented: Algebra I leads into algebra II, pre-calculus leads into calculus, and it’s all laid out right there in the textbooks, answer key in the back.

But high school and college math—even a lot of graduate school math—is a vanishingly small part of the overall knowledge. The vast majority of it is much less organized.

There are huge, important areas of math that have never been fully written down. They’re stored in the minds of a small circle of people who learned their subfield of math from people who learned it from the person who invented it—which is to say, it exists nearly as folklore.

There are other areas where the foundational material has been written down, but it’s so long and complicated that no one has been able to check that it’s fully correct. Instead, mathematicians simply have faith.

“We rely on the reputation of the author. We know he’s a genius and a careful guy, so it must be correct,” said Patrick Massot of Paris-Saclay University.

This is one reason why proof assistants are so appealing. Translating mathematics into a language a computer can understand forces mathematicians to finally catalog their knowledge and precisely define objects.

Assia Mahboubi of the French national research institute Inria recalls the first time she realized the potential of such an orderly digital library: “It was fascinating for me that one could capture, in theory, the whole mathematical literature by the sheer language of logic and store a corpus of math in a computer and check it and browse it using these pieces of software.”

Lean isn’t the first program with this potential. The first, called Automath, came out in the 1960s, and Coq, one of the most widely used proof assistants today, came out in 1989. Coq users have formalized a lot of mathematics in its language, but that work has been decentralized and unorganized. Mathematicians worked on projects that interested them and only defined the mathematical objects needed to carry their projects out, often describing those objects in unique ways. As a result, the Coq libraries feel jumbled, like an unplanned city.

[zingmagazine]

NET PLUS ULTRA at Gallery Mannerheim & Co, Paris

NET PLUS ULTRA is a group exhibition, and a “cabinet de curiosités” orchestrated by David Magnin & Géraldine Postel at the Gallery Mannerheim & Co in Paris. Between AR / VR and analog pieces works, the interpenetration of the artworks presented in this group exhibition, is linked by a thread that connects each of them with the idea of ​​a small archeology of connected art.

We start with Wolfgang Staehle, who is the first artist to have created a website for art and artists in 1995 “theThing.net”. Here he presents more recent pieces that are generated by software from data from friends’ Gmail and Facebook accounts that were "cracked." From software and data he draws the portrait of each according to the typology of their networks.

Miltos Manetas is the first painter who introduced computers or video games in painting on canvas, we had until now images of Epinal : ladies and gentlemen reading, lunches, bathing. He followed the course of things and continued to paint the world as it goes. Here, he presents drawings / theoretical slogans, such as "Outside of the Internet there is No Glory," or keyboards to which he connects the directions of the letters that make up the names of Marx, Marinetti and himself. Miltos Manetas is also founder of the NEEN group, the first 20th century artistic movement launched at Gagosian in NYC in 2003.

Rafael Rozendaal is one of the first artists to draw URLs. I exhibited him in Paris in 2003 in a project with Miltos Manetas while part of the NEEN group. Rafael Rozendaal is a visual artist and exhibits woven works reminiscent of screens. He also writes haikus, although he continues to draw URLs, these works exist on monitors of 60 inches at least, his work is today very varied and often appears in the form of installations.  

Marie Maillard has been developing digital works for several years, she has made video wallpapers, and her work is a form of exploration, a way of virtually rethinking architecture or decoration. Here she presents a piece in augmented reality, UNIT 1801, it is a PVC carpet with a motif that reproduces for target image the floor of Palazzo Grimani in Venice. She modifies colors and designs a scenography of the geometric shapes of ornamental marble tiles. We can discover them by downloading her application on iPhone or Android, and order a woven carpet or an ornamental pavement that can be also seen in enhanced reality.

Laurent Saksik’s work is based on tradition and light in painting. He has created an algorithm named RRose. This algorithm revisits a drawing by Leonardo Da Vinci, a study for portrait of a woman. RRose absorbs this portrait and Saksik proposes an interactive piece with «Codex» and the collector: the collector draws some lines and chooses a color, from there is generated a unique art piece made with four hands: Da Vinci, Saksik, Rrose, and the collector.

The contribution for DMGP Observatory (acronym: David Magnin Geraldine Postel Observatory) can be found on the Internet by watching a video, downloading the application to travel in virtual time or with a 3D headset. It is a virtual space, which introduces gamification in presenting contemporary art. We work playfully, while exploring a new territory that we have imagined as an ideal gallery under an ideal sky. It is a gallery without walls, immersed in nature, standing by a lake and surrounded by mountains. We have a day / night rotation and added aurora borealis. It's a kind of a Jungian project, which connects cognitive and behavioral: first to escape the constraint of staying there, stuck in a gallery waiting for the collector or the journalist to come and see what is proposed. No more excuses not to come to the opening, not to be in the area the time of the exhibition, everything is in cyberspace, if you are curious, you can connect at any time . . . DMGP Observatory, is our command from David Magnin and myself, it is developed by Arnaud Pepin-Donat. David and I present our personal collections to continue to share and make the art works circulate, which once purchased, often remain in our closed interiors, and have no more public visibility you can visit at: www.DMGPobservatory.com

Prototypes and other projects are added to produce them for collectors, such as David Ancelin's "Acapulco", a hybrid piece between Le Corbusier's chaise lounge and Charlotte Perriand's Bauche chair. This space is also a communicating object because it gives the beginnings of a residence space that one would like to build in the mountains in a similar landscape, to invite artists and craftsmen to work there, to draw inspiration and to rest together. We are opening today with a first submission for the call for projects by artists and architects Dejode & Lacombe who proposed their Château Entremont, a small castle built of recycled containers and wood, a sustainable, economic and ecological habitat that could to be the first shelter or turn of rendez-vous of our utopian space, which we are still looking for in the Alps. The multidisciplinary artist Arnaud Pepin-Donat also developed the AR image for the Dejode & Lacombe t-shirt that we sell to support our residency project. He also designed the AR image of the Japanese designer's dress by Nao Okawa. This dress comes from collaboration with the Le Coq Sportif Japan. It also presents one of these drawings of a precise and almost imperceptible vision of an interstellar space in AR . . .

Finally, others like Devon Dikeou and Nora Renaud present analog pieces:

Devon Dikeou develops a conceptual and often interactive work that involves the viewer and connects people to them. This work is revealed here through a signboard that is still found in the entrance halls of US buildings. This signboard lists the context of NET PLUS ULTRA, the date, the gallery, the curators, the invited artists, making this work the subject of the invitation, even if she is not a digital artist, her work connects each of the protagonists in time . . .

David Ancelin presents "Summer Wine" a play with strong Dada connotations, a wink that connects the past to the present and the temporal exploration: an amphora and a diver's palm that would have drunk all wine or nectar during its exploration. It is also a reminder to our consumer society that engulfs everything it touches and if it does not seize it, it destroys nature and history, and even the rarest things . . . Summer Wine is a piece being integrated into our online observatory that responds to "Acapulco" the lounge chair I mentioned earlier.

For Nora Renaud, she imagines a life without internet, or post internet, as an end of the World announced where we would find objects like this carcass of iPhone in Bronze, a similar computer in wood painted like a trace left by men who would like to write the story. Or a synthetic fur rug that is an imaginary aesthetic of possible future modern cavemen who remember the # as a powerful symbol.

Some works are more politically engaged than others, they are all in their own way, moreover it is what motivates us and makes us appreciate the work of these artists who do not only offer a decorative work. These works tell a story, our story. For us, to continue a reflection on the system, the world in evolution or degradation, is essential. We are all engaged artists in one way or another. As far as we are concerned, we have done humble curators work in a small Parisian gallery that gives a narrative meaning and connects these works that touch a field still unknown, even if new technologies, URL, AR and VR in art is not completely new since the history shows it to us here. This field of expression is not always perceived as a work because it presents itself in a different way but it is also a new way of existing over time. NET PLUS ULTRA: is a group exhibition of visual artists, designers, theoreticians and sorcerer’s apprentices of a new era. It is also the portrait of a group of big turbulents.  

The exhibition is open until May 12, 2019

Géraldine Postel, Paris April 2019

[krupeshkotak]

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Imp definition

#Imp definition how to

#Imp definition tv

These example sentences are selected automatically from various online news sources to reflect current usage of the word 'impish.' Views expressed in the examples do not represent the opinion of Merriam-Webster or its editors. Here is a familiar mathematical function written in Imp. Our case study is a simple imperative programming language called Imp, embodying a tiny core fragment of conventional mainstream languages such as C and Java.

#Imp definition how to

Robert Abele, Los Angeles Times, Mandel delivers this futuristic section with an impish blend of wit and dread. In this chapter, we take a more serious look at how to use Coq as a tool to study other things. Robyn Bahr, The Hollywood Reporter, The boy’s impish defiance, coupled with the weary father’s wry handling of it, kick-starts the movie’s delightful strain of rambunctious-kid comedy.

#Imp definition tv

Manuel Roig-franzia, Washington Post, 8 June 2022 Goncalves is an excellent anchor, combining the impish pique of a kid with a sense of how to deliver a punchline that belies her youth.ĭaniel D'addario, Variety, 22 June 2022 While politicized coffee klatch shows like The View continue to cycle through hosts and heart-healing former daytime deity Oprah Winfrey has long since moved on to larger TV mogul ventures, Ellen remained a stalwart hour for impish escapism. Barriers to Entry Definition-A barrier to entry is simply an obstacle that new businesses face when entering the market. They are usually described as lively and having small stature. The attendants of the devil are sometimes described as imps. Imps are often described as troublesome and mischievous more than seriously threatening or dangerous, and as lesser beings rather than more important supernatural beings. The word may perhaps derive from the term ympe, used to denote a young grafted tree. So when a good arrives at customs from sea, plane, or motor vehicle, an import tax is due based upon the current ‘schedule’. An imp is a European mythological being similar to a fairy or demon, frequently described in folklore and superstition. New York Times, 31 July 2022 By the 1970s, this charmer with the impish smile had been driving a taxi in Washington for more than three decades. A tariff is an import tax on goods coming into a country. 1 2 3 An IMP was a ruggedized Honeywell DDP-516 minicomputer with special-purpose interfaces and software. It was the first generation of gateways, which are known today as routers. 2022 With his infectious enthusiasm and impish smile, Price seems a natural choice. The Interface Message Processor ( IMP) was the packet switching node used to interconnect participant networks to the ARPANET from the late 1960s to 1989. Choose the location for the file to import: The file must be in the import folder on your FTP and its name must match what you entered in the file naming pattern. Click Create and select data extension, list, or chat messaging as the destination for your data. Numbers do not necessarily match those in definitions. Follow these steps to create an import definition in Marketing Cloud Contact Builder. 2022 Among them sat Maksym Kryshtafor, an 8-year-old Ukrainian boy with freckles and an impish smile, who navigated his pieces across the board with intense focus. imp (third-person singular simple present imps, present participle imping, simple past and past. Recent Examples on the Web In the first three half-hour episodes sent to critics, Little Demon can be wobbly in balancing its impish sense of humor and squishy sense of heart, its otherworldly shenanigans and its more grounded emotions.Īngie Han, The Hollywood Reporter, 25 Aug.