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1 666 shares, 69 trendiness

Daniel Dennett (1942-2024)

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news for & about the phi­los­o­phy pro­fes­sion

Daniel Dennett, pro­fes­sor emer­i­tus of phi­los­o­phy at Tufts University, well-known for his work in phi­los­o­phy of mind and a wide range of other philo­soph­i­cal ar­eas, has died.

Professor Dennett wrote ex­ten­sively about is­sues re­lated to phi­los­o­phy of mind and cog­ni­tive sci­ence, es­pe­cially con­scious­ness. He is also rec­og­nized as hav­ing made sig­nif­i­cant con­tri­bu­tions to the con­cept of in­ten­tion­al­ity and de­bates on free will. Some of Professor Dennett’s books in­clude Content and Consciousness (1969), Brainstorms: Philosophical Essays on Mind and Psychology (1981), The Intentional Stance (1987), Consciousness Explained (1992), Darwin’s Dangerous Idea (1995), Breaking the Spell (2006), and From Bacteria to Bach and Back: The Evolution of Minds (2017). He pub­lished a mem­oir last year en­ti­tled I’ve Been Thinking. There are also sev­eral books about him and his ideas. You can learn more about his work here.

Professor Dennett held a po­si­tion at Tufts University for nearly all his ca­reer. Prior to this, he held a po­si­tion at the University of California, Irvine from 1965 to 1971. He also held vis­it­ing po­si­tions at Oxford, Harvard, Pittsburgh, and other in­sti­tu­tions dur­ing his time at Tufts University. Professor Dennett was awarded his PhD from the University of Oxford in 1965 and his un­der­grad­u­ate de­gree in phi­los­o­phy from Harvard University in 1963.

Professor Dennett is the re­cip­i­ent of sev­eral awards and prizes in­clud­ing the Jean Nicod Prize, the Mind and Brain Prize, and the Erasmus Prize. He also held a Fulbright Fellowship, two Guggenheim Fellowships, and a Fellowship at the Center for Advanced Study in Behavioral Sciences. An out­spo­ken athe­ist, Professor Dennett was dubbed one of the Four Horsemen of New Atheism”. He was also a Fellow of the Committee for Skeptical Inquiry, an hon­ored Humanist Laureate of the International Academy of Humanism, and was named Humanist of the Year by the American Humanist Organization.

He died this morn­ing from com­pli­ca­tions of in­ter­sti­tial lung dis­ease.*

The fol­low­ing in­ter­view with Professor Dennett was recorded last year:

Related: Philosophers: Stop Being Self-Indulgent and Start Being Like Daniel Dennett, says Daniel Dennett“. (Other DN posts on Dennett can be found here.)

*This was added af­ter the ini­tial pub­li­ca­tion of the post. Source: New York Times.

The eth­i­cal aca­d­e­mic should be op­posed to most of our cur­rent grad­ing prac­tices, but they still need to grade stu­dents any­way”

– John Danaher (Galway) on the whats, whys, and hows of eth­i­cal grad­ing

Kant saw rea­son’s po­ten­tial as a tool for lib­er­a­tion”

– Susan Neiman (Einstein Forum) in the NYT on why we should cel­e­brate Kant

Assisted evo­lu­tion is… an ac­knowl­edg­ment that there is no step­ping back, no fu­ture in which hu­mans do not pro­foundly shape the lives and fates of wild crea­tures”

– new ways of pro­tect­ing an­i­mals raise ques­tions about what con­ser­va­tion is and what species are

Metaphysics be­gins with the dis­tinc­tion be­tween ap­pear­ance and re­al­ity, be­tween seems and is, and the play con­stantly plays with this dis­tinc­tion”

– Brad Skow (MIT) on the phi­los­o­phy in Hamlet

Beliefs aim at the truth, you say?

– the New Yorker cov­ers work by philoso­phers and oth­ers in an ar­ti­cle about the com­pli­ca­tions of mis­in­for­ma­tion

Philosophical the­o­ries are very much like pictures’ or stories’ and… philo­soph­i­cal de­bates of­ten come down to temperamental dif­fer­ences’”

– Peter West (Northeastern U. London) on the metaphi­los­o­phy of Margaret MacDonald

The swift­ness and ease of the tech­nol­ogy sep­a­rates peo­ple from the re­al­ity of what they are tak­ing part in”

– and there’s a lot go­ing on

Any sur­pris­ing re­sults sci­en­tists achieved, whether they sup­ported or chal­lenged a pre­vi­ous as­sump­tion, were seen as the ul­ti­mate source of aes­thetic plea­sure”

– Milena Ivanova (Cambridge) on the role of aes­thet­ics in sci­ence

I could­n’t have jus­ti­fied spend­ing a ca­reer as an aca­d­e­mic philoso­pher. Not in this world.”

– Nathan J. Robinson on the im­moral­ity of phi­los­o­phy in a time of cri­sis

Within the ring of light lies what is straight­for­wardly know­able through com­mon sense or main­stream sci­ence” but phi­los­o­phy lives in the penum­bra of dark­ness”

– and even as that light grows, says Eric Schwitzgebel (UC Riverside), just be­yond it there will al­ways be dark­ness”–-and phi­los­o­phy

The sci­en­tific com­mu­nity has gen­er­ally done a poor job of ex­plain­ing to the pub­lic that sci­ence is what is known so far”

– H. Holden Thorp, the ed­i­tor in chief of Science, on why the his­tory and phi­los­o­phy of sci­ence should be part of the sci­ence cur­ricu­lum (via Nathan Nobis)

– Tamar Gendler (Yale) dis­cusses an ex­per­i­men­tal course she taught on phi­los­o­phy and its forms

If you’re go­ing to be a philoso­pher, learn about the world, learn about the sci­ence… Scientists are just as ca­pa­ble of mak­ing philo­soph­i­cal mis­takes… as any lay peo­ple [and] they need the help of in­formed philoso­phers”

I’m cu­ri­ous about why these kinds of places have such a spell­bind­ing aura, and I think it’s be­cause they are ana­log out­liers”

– Evan Selinger (RIT) re­flects on his ob­ses­sion with a small-town fam­ily-run ho­tel that serves sim­ple and de­li­cious food

The story that a sports fan en­gages with is a col­lab­o­ra­tively writ­ten story; [it is] a so­cial en­ter­prise fo­cused around knit­ting in­di­vid­ual games into nar­ra­tive arcs, sto­ries, leg­ends, and char­ac­ter­i­za­tions”

– Peter Kung and Shawn Klein (ASU) on imag­i­na­tion and sports fan­dom

Claude 3 Opus pro­duces ar­gu­ments that don’t sta­tis­ti­cally dif­fer in their per­sua­sive­ness com­pared to ar­gu­ments writ­ten by hu­mans”

– the meth­ods and re­sults of a study on AI per­sua­sive­ness

Limiting virtues [are] virtues that con­strain us in or­der to set us free”

– Sara Hendren (Northeastern), in­spired by David McPherson (Creighton) looks for lim­it­ing virtues in ar­chi­tec­ture

It is not only false but morally mis­lead­ing to de­scribe the re­sult­ing civil­ian deaths as unintentional’ or as what happens in war’”

– Jessica Wolfendale (Case Western) on the tools and tac­tics used in Gaza by Israel’s mil­i­tary

Both were an­a­lyt­i­cal philoso­phers, but their in­tel­lec­tual frame­works and their philo­soph­i­cal ap­proaches were markedly dif­fer­ent”

– Dan Little (UM-Dearborn) on Popper and Parfit

El Salvador seeks philoso­phers (and doc­tors, sci­en­tists, en­gi­neers, artists, and oth­ers)

– the na­tion’s pres­i­dent has of­fered 5000 free pass­ports along with tax ben­e­fits to those an­swer­ing his call

He has awak­ened us to the back­ground prac­tices in our cul­ture, and re­vealed to us that they have no ne­ces­sity, which of­fers us a kind of free­dom we may not have rec­og­nized”

– Mark Ralkowski (GWU) on the phi­los­o­phy of Larry David

I think [NASAs] re­quire­ments are clos­ing the as­tro­naut pro­gram off from im­por­tant in­sights from the hu­man­i­ties and so­cial sci­ences”

– a phi­los­o­phy PhD and US Air Force of­fi­cer on why we should send philoso­phers into space

Before he was the lit­tle guy who spake about teach­ing of the Superman, he ap­peared in Nietzsche’s book The Gay Science’” Who is….?”

– phi­los­o­phy was a cat­e­gory in the sec­ond round of Jeopardy!” ear­lier this week (mouse over the $ to see the an­swers, er ques­tions)

Can phi­los­o­phy be done through nar­ra­tive films like Barbie?”

– that de­pends on what we mean by do­ing phi­los­o­phy, says Tom McClelland (Cambridge)

There is no moral va­lence to some­one just not lik­ing us.” There’s a good­ness and rich­ness in this sort of pre­des­tined suf­fer­ing.”

– the moral sen­si­bil­i­ties of Lillian Fishman, ad­vice colum­nist at The Point

Philosophers write a lot about friend­ship and love, but they tend to do so in terms that leave out the cen­tral­ity of the heart and heart­felt con­nec­tion”

– as a re­sult, says Stephen Darwall (Yale), we miss some im­por­tant things

Wenar’s al­ter­na­tive to ef­fec­tive al­tru­ism is nei­ther vi­able nor de­sir­able nor in­deed any im­prove­ment on ef­fec­tive al­tru­ism”

While the shal­low pond may be a good model to help us think about our im­me­di­ate du­ties, it is a bad model to help us think about the re­la­tion­ship be­tween would be donors and the suf­fer­ing poor in the con­text of de­vel­op­ment”

– Eric Schliesser (Amsterdam) on Richard Pettigrew on Leif Wenar on ef­fec­tive al­tru­ism

...

Read the original on dailynous.com »

2 389 shares, 29 trendiness

Tesla recalls the Cybertruck for faulty accelerator pedals that can get stuck

Tesla is re­call­ing all 3,878 Cybertrucks that it has shipped to date, due to a prob­lem where the ac­cel­er­a­tor pedal can get stuck, putting dri­vers at risk of a crash, ac­cord­ing to the National Highway Traffic Safety Administration.

The re­call caps a tu­mul­tuous week for Tesla. The com­pany laid off more than 10% of its work­force on Monday, and lost two of its high­est-rank­ing ex­ec­u­tives. A few days later, Tesla asked share­hold­ers to re-vote on CEO Elon Musk’s mas­sive com­pen­sa­tion pack­age that was struck down by a judge ear­lier this year.

Reports of prob­lems with the Cybertruck’s ac­cel­er­a­tor pedal started pop­ping up in the last few weeks. Tesla even re­port­edly paused de­liv­er­ies of the truck while it sorted out the is­sue. Musk said in a post on X that Tesla was being very cau­tious” and the com­pany re­ported to NHTSA that it was not aware of any crashes or in­juries re­lated to the prob­lem.

The com­pany has now con­firmed to NHTSA that the pedal can dis­lodge, mak­ing it pos­si­ble for it to slide up and get caught in the trim around the footwell.

Tesla said it first re­ceived a no­tice of one of these ac­cel­er­a­tor pedal in­ci­dents from a cus­tomer on March 31, and then a sec­ond one on April 3. After per­form­ing a se­ries of tests, it de­cided on April 12 to is­sue a re­call af­ter de­ter­min­ing that [a]n un­ap­proved change in­tro­duced lu­bri­cant (soap) to aid in the com­po­nent as­sem­bly of the pad onto the ac­cel­er­a­tor pedal,” and that [r]esidual lu­bri­cant re­duced the re­ten­tion of the pad to the pedal.”

Tesla says it will re­place or re­work the ac­cel­er­a­tor pedal on all ex­ist­ing Cybertrucks. It also told NHTSA that it has started build­ing Cybertrucks with a new ac­cel­er­a­tor pedal, and that it’s fix­ing the ve­hi­cles that are in tran­sit or sit­ting at de­liv­ery cen­ters.

While the Cybertruck only first started ship­ping late last year, this is not the ve­hi­cle’s first re­call. But the ini­tial one was mi­nor: Earlier this year, Tesla re­called the soft­ware on all of its ve­hi­cles be­cause the font sizes of its warn­ing lights were too small. The com­pany un­veiled the truck back in 2019.

...

Read the original on techcrunch.com »

3 385 shares, 20 trendiness

now supports the S3 protocol

Supabase Storage is now of­fi­cially an S3-Compatible Storage Provider. This is one of the most-re­quested fea­tures and is avail­able to­day in pub­lic al­pha. Resumable Uploads are also tran­si­tion­ing from Beta to Generally Available.

The Supabase Storage Engine is fully open source and is one of the few stor­age so­lu­tions that of­fer 3 in­ter­op­er­a­ble pro­to­cols to man­age your files:

* S3 up­loads: for com­pat­i­bil­ity across a plethora of tools

We al­ways strive to adopt in­dus­try stan­dards at Supabase. Supporting stan­dards makes work­loads portable, a key prod­uct prin­ci­ple. The S3 API is un­doubt­edly a stor­age stan­dard, and we’re mak­ing it ac­ces­si­ble to de­vel­op­ers of var­i­ous ex­pe­ri­ence-lev­els.

The S3 pro­to­col is back­wards com­pat­i­ble with our other APIs. If you are al­ready us­ing Storage via our REST or TUS APIs, to­day you can use any S3 client to in­ter­act with your buck­ets and files: up­load with TUS, serve them with REST, and man­age them with the S3 pro­to­col.

The pro­to­col works on the cloud, lo­cal de­vel­op­ment, and self-host­ing. Check out the API com­pat­i­bil­ity in our docs

To au­then­ti­cate with Supabase S3 you have 2 op­tions:

The stan­dard ac­cess_key and se­cret_key cre­den­tials. You can gen­er­ate these from the stor­age set­tings page. This au­then­ti­ca­tion method is widely com­pat­i­ble with tools sup­port­ing the S3 pro­to­col. It is also meant to be used ex­clu­sively server­side since it pro­vides full ac­cess to your Storage re­sources.

We will add scoped ac­cess key cre­den­tials in the near fu­ture which can have ac­cess to spe­cific buck­ets.

User-scoped cre­den­tials with RLS. This takes ad­van­tage of a well-adopted con­cept across all Supabase ser­vices, Row Level Security. It al­lows you to in­ter­act with the S3 pro­to­col by scop­ing stor­age op­er­a­tions to a par­tic­u­lar au­then­ti­cated user or role, re­spect­ing your ex­ist­ing RLS poli­cies. This method is made pos­si­ble by us­ing the Session to­ken header which the S3 pro­to­col sup­ports. You can find more in­for­ma­tion on how to use the Session to­ken mech­a­nism in the doc.

With the sup­port of the S3 pro­to­col, you can now con­nect Supabase Storage to many 3rd-party tools and ser­vices by pro­vid­ing a pair of cre­den­tials which can be re­voked at any time.

You can use pop­u­lar tools for back­ups and mi­gra­tions, such as:

* and any other s3-com­pat­i­ble tool …

Check out our Cyberduck guide here.

S3 com­pat­i­bil­ity pro­vides a nice prim­i­tive for Data Engineers. You can use it with many pop­u­lar tools:

In this ex­am­ple our in­cred­i­ble data an­a­lyst, Tyler, demon­strates how to store Parquet files in Supabase Storage and query them di­rectly us­ing DuckDB:

In ad­di­tion to the stan­dard up­loads and re­sum­able up­loads, we now sup­port mul­ti­part up­loads via the S3 pro­to­col. This al­lows you to max­i­mize up­load through­put by up­load­ing chunks in par­al­lel, which are then con­cate­nated at the end.

Along with the plat­form GA an­nounce­ment, we are also thrilled to an­nounce that re­sum­able up­loads are also gen­er­ally avail­able.

Resumable up­loads are pow­ered by the TUS pro­to­col. The jour­ney to get here was im­mensely re­ward­ing, work­ing closely with the TUS team. A big shoutout to the main­tain­ers of the TUS pro­to­col, @murderlon and @acconut, for their col­lab­o­ra­tive ap­proach to open source.

Supabase con­tributed some ad­vanced fea­tures from the Node im­ple­men­ta­tion of TUS Spec in­clud­ing dis­trib­uted locks, max file size, ex­pi­ra­tion ex­ten­sion and nu­mer­ous bug fixes:

These fea­tures were es­sen­tial for Supabase, and since the TUS node server is open source, they are also avail­able for you to use. This is an­other core prin­ci­ple: wher­ever pos­si­ble, we use and sup­port ex­ist­ing tools rather than de­vel­op­ing from scratch.

* Cross-bucket trans­fers: We have added the avail­abil­ity to copy and move ob­jects across buck­ets, where pre­vi­ously you could do these op­er­a­tions only within the same Supabase bucket.

* Standardized er­ror codes: Error codes have now been stan­dard­ized across the Storage server and now will be much eas­ier to branch logic on spe­cific er­rors. You can find the list of er­ror codes here.

* Multi-tenant mi­gra­tions: We made sig­nif­i­cant im­prove­ments to the run­ning mi­gra­tions across all our ten­ants. This has re­duced mi­gra­tion er­rors across the fleet and en­ables us to run long run­ning mi­gra­tions in an asyn­chro­nous man­ner. Stay tuned for a sep­a­rate blog post with more de­tails.

* Decoupled de­pen­den­cies: Storage is fully de­cou­pled from other Supabase prod­ucts, which means you can run Storage as a stand­alone ser­vice. Get started with this docker-com­pose file.

...

Read the original on supabase.com »

4 235 shares, 17 trendiness

Blurmatic

...

Read the original on www.blurmatic.com »

5 234 shares, 32 trendiness

Your powerful rich text editor

Used in small pro­jects and gi­ant Fortune 500s alike. Start sim­ple with the Quill core then eas­ily cus­tomize or add your own ex­ten­sions later if your prod­uct needs grow.

Learn More

...

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6 225 shares, 21 trendiness

Programming -- Principles and Practice Using C++ (3rd Edition)

Modified April 18, 2024.

Programming — Principles and Practice Using C++ (3rd Edition)

You can buy di­rectly from the pub­lisher.

Programming: Principles and Practice Using C++, Third Edition, will help any­one who is will­ing to work hard learn the fun­da­men­tal prin­ci­ples of pro­gram­ming and de­velop the prac­ti­cal skills needed for pro­gram­ming in the real world. Previous edi­tions have been used suc­cess­fully by many thou­sands of stu­dents. This re­vised and up­dated edi­tion

Assumes that your aim is to even­tu­ally write pro­grams that are good enough for oth­ers to use

and main­tain

Focuses on fun­da­men­tal con­cepts and tech­niques, rather than on ob­scure lan­guage-tech­ni­cal de­tails

Is an in­tro­duc­tion to pro­gram­ming in gen­eral, in­clud­ing pro­ce­dural, ob­ject-ori­ented, and generic

pro­gram­ming, rather than just an in­tro­duc­tion to a pro­gram­ming lan­guage

Covers both con­tem­po­rary high-level tech­niques and the lower-level tech­niques needed for ef­fi­cient

use of hard­ware

Will give you a solid foun­da­tion for writ­ing use­ful, cor­rect, type-safe, main­tain­able, and ef­fi­cient code

Is pri­mar­ily de­signed for peo­ple who have never pro­grammed be­fore, but even sea­soned pro­gram­mers

have found pre­vi­ous edi­tions use­ful as an in­tro­duc­tion to more ef­fec­tive con­cepts and tech­niques

Covers the de­sign and use of both built-in types and user-defi ned types, com­plete with in­put,

out­put, com­pu­ta­tion, and sim­ple graph­ics/​GUI

Offers an in­tro­duc­tion to the C++ stan­dard li­brary con­tain­ers and al­go­rithms

ABOUT THE AUTHOR Bjarne Stroustrup is the de­signer and orig­i­nal im­ple­menter of C++, as well as the au­thor of

The C++ Programming Language and

A Tour of C++, and many pop­u­lar and aca­d­e­mic pub­li­ca­tions. He is a pro­fes­sor of Computer Science at Columbia University in New York City. Dr. Stroustrup is a mem­ber of the US National Academy of Engineering, and an IEEE, ACM, and CHM fel­low. He re­ceived the 2018 Charles Stark Draper Prize, the IEEE Computer Society’s 2018 Computer Pioneer Award, and the 2017 IET Faraday Medal.

Programming: Principles and Practice us­ing C++ (3rd Edition)”, aka PPP3,

is an in­tro­duc­tion to pro­gram­ming for peo­ple who have never pro­grammed be­fore.

It will also be use­ful for peo­ple who have pro­grammed a bit and want to im­prove

their style and tech­nique - or sim­ply learn mod­ern C++.

It is de­signed for class­room use, but writ­ten with an eye on self study.

Ealier ver­sions of this book

have been used as the ba­sis for first pro­gram­ming classes for elec­tri­cal en­gi­neer­ing,

com­puter en­gi­neer­ing, and com­puter sci­ence stu­dents at Texas A&M University and in many other places.

People who have seen PPP2 will no­tice that PPP3 is about half its size. What I have done to keep the weight down is to

strengthen the foun­da­tional chap­ters usu­ally cov­ered in a one-se­mes­ter course,

uti­liz­ing key parts of C++20 and C+23,

and re-bas­ing the Graphics/GUI chap­ter code on

Qt

for porta­bil­ity (e.g., to browsers and phones).

placed the more spe­cial­ized chapers (known as broadening the view” in PPP2) on the Web for peo­ple to use as needed.

See be­low.

elim­i­nate the pure ref­er­ence ma­te­r­ial.

You now can find more and more up-to-date ma­te­r­ial on the web, e.g.

cp­pref­er­ence.com.

The

sup­port­ing ma­te­r­ial for PPP2 is avail­able as ever (lecture slides, code, etc.).

Here are some PPP3 sam­ples

Preface.

What the book promises, and what it does not promise.

Chapter 0: Notes to the Reader.

Some notes on the ap­proach taken by the book.

Chapter 10: A Display Model.

A sam­ple chap­ter.

If you are a real novice, don’t read this chap­ter quite yet.

I post it to show teach­ers and more ex­pe­ri­enced read­ers where the book gets to in the 5th week or so (assuming two chap­ters a week).

Also, to show off a lit­tle bit of con­tem­po­rary C++.

These chap­ters were writ­ten us­ing C++14, rather than C++23, but are still cor­rect and in­tro­duce their top­ics in a rea­son­able man­ner.

None yet. See my book cov­ers page for trans­la­tions of ear­lier edi­tions.

...

Read the original on www.stroustrup.com »

7 222 shares, 9 trendiness

The SeaMonkey® Project

Web-browser, ad­vanced e-mail, news­group and feed client, IRC chat, and HTML edit­ing made sim­ple—all your Internet needs in one ap­pli­ca­tion.

Which op­er­at­ing sys­tem are you us­ing?

Would you like to se­lect a dif­fer­ent lan­guage?

The SeaMonkey pro­ject is a com­mu­nity ef­fort to de­velop the SeaMonkey Internet Application Suite (see be­low). Such a soft­ware suite was pre­vi­ously made pop­u­lar by Netscape and Mozilla, and the SeaMonkey pro­ject con­tin­ues to de­velop and de­liver high-qual­ity up­dates to this con­cept. Containing an Internet browser, email & news­group client with an in­cluded web feed reader, HTML ed­i­tor, IRC chat and web de­vel­op­ment tools, SeaMonkey is sure to ap­peal to ad­vanced users, web de­vel­op­ers and cor­po­rate users.

Under the hood, SeaMonkey uses much of the same Mozilla Firefox source code which pow­ers such prod­ucts as

Thunderbird. Legal back­ing is pro­vided by the SeaMonkey Association (SeaMonkey e. V.).

The SeaMonkey pro­ject is proud to pre­sent SeaMonkey 2.53.18.2: The new re­lease of the all-in-one Internet suite is

avail­able for free down­load now!

2.53.18.2 is a mi­nor bug­fix re­lease on the 2.53.x branch and con­tains a crash fix and a few other fixes to the ap­pli­ca­tion from the un­der­ly­ing plat­form code.

SeaMonkey 2.53.18.2 is avail­able in 23 lan­guages, for Windows, ma­cOS x64 and Linux.

Automatic up­grades from pre­vi­ous 2.53.x ver­sions are en­abled for this

re­lease, but if you have prob­lems with it please down­load the full in­staller

from the down­loads sec­tion and in­stall SeaMonkey 2.53.18.2 man­u­ally over the

pre­vi­ous ver­sion.

For a more com­plete list of ma­jor changes in SeaMonkey 2.53.18.2, see the

What’s New in SeaMonkey 2.53.18.2

sec­tion of the Release Notes, which also con­tains a list of known is­sues and an­swers to fre­quently asked ques­tions. For a more gen­eral overview of the SeaMonkey pro­ject (and screen shots!), visit www.sea­mon­key-pro­ject.org.

We en­cour­age users to get in­volved in dis­cussing and re­port­ing prob­lems as well as fur­ther im­prov­ing the prod­uct.

The SeaMonkey pro­ject is proud to pre­sent SeaMonkey 2.53.18 Beta 1: The new beta test re­lease of the all-in-one Internet suite is

avail­able for free down­load now!

2.53.18 will be an in­cre­men­tal up­date on the 2.53.x branch and in­cor­po­rates a num­ber of en­hance­ments, changes and fixes to the ap­pli­ca­tion as well as those from the un­der­ly­ing plat­form code. Support for pars­ing and pro­cess­ing newer reg­exp ex­pres­sions has been added help­ing with web com­pat­i­bil­ity on more than a few sites. Crash re­port­ing has been switched over to

BugSplat. We also added many fixes and back­ports for over­all plat­form sta­bil­ity.

Before in­stalling the new ver­sion make a full backup of

your pro­file and thor­oughly read and fol­low the

Release Notes. We en­cour­age testers to get in­volved in dis­cussing and re­port­ing prob­lems as well as fur­ther im­prov­ing the prod­uct.

SeaMonkey 2.53.18 Beta 1 is avail­able in 23 lan­guages, for Windows, ma­cOS x64 and Linux.

Attention ma­cOS users! The cur­rent SeaMonkey re­lease crashes dur­ing startup af­ter up­grad­ing to ma­cOS 13 Ventura. Until we have a fix we ad­vise you not to up­grade your ma­cOS in­stal­la­tion to Ventura. No us­able crash in­for­ma­tion is gen­er­ated and this might take a bit longer than usual to fix. This is not a prob­lem with Monterey 12.6.1 or any lower sup­ported ma­cOS ver­sion so might even be an Apple bug.

SeaMonkey has in­her­ited the suc­cess­ful all-in-one con­cept of the orig­i­nal Netscape Communicator and con­tin­ues that prod­uct line based on the mod­ern, cross-plat­form ar­chi­tec­ture pro­vided by the

Mozilla pro­ject.

* The Internet browser at the core of

the SeaMonkey Internet Application Suite uses the same ren­der­ing en­gine and

ap­pli­ca­tion plat­form as Mozilla Firefox, with pop­u­lar fea­tures like tabbed

brows­ing, feed de­tec­tion, popup block­ing, smart lo­ca­tion bar, find as you

type and a lot of other func­tion­al­ity for a smooth web ex­pe­ri­ence.

* SeaMonkey’s Mail and Newsgroups client

shares lots of code with Thunderbird and fea­tures adap­tive Junk mail

fil­ter­ing, tags and mail views, web feeds read­ing, tabbed mes­sag­ing, mul­ti­ple

ac­counts, S/MIME, ad­dress books with LDAP sup­port and is ready for both

pri­vate and cor­po­rate use.

* Additional com­po­nents in­clude an easy-to-use

HTML Editor, the ChatZilla IRC chat

ap­pli­ca­tion and web de­vel­op­ment tools like a DOM Inspector.

* If that’s still not enough, SeaMonkey can be ex­tended with nu­mer­ous

Add-Ons that pro­vide

ad­di­tional func­tion­al­ity and cus­tomiza­tion for a com­plete Internet

ex­pe­ri­ence.

...

Read the original on www.seamonkey-project.org »

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Discover the vast ranges of our visible and invisible world.

Scale of Universe is an in­ter­ac­tive ex­pe­ri­ence to in­spire peo­ple to learn about the vast ranges of the vis­i­ble and in­vis­i­ble world. Click on ob­jects to learn more. Use the scroll bar to zoom in and out. Remastered by Dave Caruso, Ben Plate, and more.

...

Read the original on scaleofuniverse.com »

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The state of AI for hand-drawn animation inbetweening

The state of AI for hand-drawn an­i­ma­tion in­be­tween­ing

There are many po­ten­tial ways to use AI

(and com­put­ers in gen­eral) for 2D an­i­ma­tion. I’m cur­rently in­ter­ested in a seem­ingly con­ser­v­a­tive goal: to im­prove the

pro­duc­tiv­ity of a tra­di­tional hand-drawn full an­i­ma­tion work­flow by AI as­sum­ing re­spon­si­bil­i­ties sim­i­lar to those of a hu­man

as­sis­tant.

As a sub-goal” of that larger goal, we’ll take a look at two re­cently pub­lished pa­pers on an­i­ma­tion inbetweening” — the au­to­matic gen­er­a­tion of in­ter­me­di­ate frames be­tween given keyframes. AFAIK these pa­pers rep­re­sent the cur­rent state of the art. We’ll see how these pa­pers and a com­mer­cial frame in­ter­po­la­tion tool per­form on some test se­quences. We’ll then briefly dis­cuss the fu­ture of the broad fam­ily of tech­niques in these pa­pers ver­sus some sub­stan­tially dif­fer­ent emerg­ing ap­proaches.

There’s a lot of other rel­e­vant re­search to look into, which I’m try­ing to do - this is just the start. I should say that I’m not an AI guy” - or rather I am if you’re build­ing an in­fer­ence chip, but not if you’re train­ing a neural net. I’m in­ter­ested in this as a pro­gram­mer who could in­cor­po­rate the lat­est tech into an an­i­ma­tion pro­gram, and as an an­i­ma­tor who could use that pro­gram. But I’m no ex­pert on this, and so I’ll be very happy to get feed­back/​sug­ges­tions through email or com­ments.

I’ve been into an­i­ma­tion tech since for­ever, and what’s pos­si­ble these days is ex­cit­ing. Specifically with in­be­tween­ing tech, I think we’re still not there yet”, and I think you’ll agree af­ter see­ing the re­sults be­low. But we might well get there within a decade, and maybe much sooner.

I think this stuff is very, very in­ter­est­ing! If you think so, too, we should get in touch. Doubly so if you want to work on this. I am go­ing to work on ex­actly this!

Why is it in­ter­est­ing to make AI a 2D an­i­ma­tor’s as­sis­tant, of all the things we could have it do (text to video, im­age to video, im­age style trans­fer onto a video, etc.)?

* An an­i­ma­tor is an ac­tor. The mo­tion of a char­ac­ter re­flects the im­plied phys­i­cal and men­tal state of that

char­ac­ter. If the mo­tion of a char­ac­ter, even one de­signed by a hu­man, is fully ma­chine-gen­er­ated, it means that hu­man con­trol

over act­ing is lim­ited; the ma­chine is now the ac­tor, and the hu­man’s in­flu­ence is lim­ited to directing” at best. It is

in­ter­est­ing to de­velop AI-assisted work­flows where the hu­man is still the ac­tor.

* To con­trol mo­tion, the an­i­ma­tor needs to draw sev­eral keyframes (or per­haps edit a ma­chine-gen­er­ated draft

- but with a pos­si­bil­ity to erase and re­draw it fully.) The range of ways to do a sad walk” or an an­gry, sur­prised head turn”

and the range of char­ac­ter traits in­flu­enc­ing the act­ing is too wide for act­ing to be con­trolled via cues other than ac­tu­ally

draw­ing the pose.

* If a hu­man is to be in con­trol, moving line art” is the nec­es­sary ba­sis for any in­no­va­tions in the ap­pear­ance of

the char­ac­ters. That’s be­cause hu­mans use a light table”, aka onion skin”, to draw mov­ing char­ac­ters, where you see

sev­eral frames over­laid on top of each other (like the frames of a bounc­ing ball se­quence be­low). And it’s roughly not hu­manly

pos­si­ble to read” a light table un­less the frames have the sharp edges of line art (believe me, I spent more time try­ing than I

should have.) Any work­flow with hu­man an­i­ma­tors in con­trol of mo­tion needs to have line art at its ba­sis, even if the fi­nal

ren­dered film looks very dif­fer­ently from the tra­di­tional line art style.

* The above gives the hu­man a role sim­i­lar to a tra­di­tional key an­i­ma­tor, so it’s nat­ural to give the ma­chine the

roles of as­sis­tants. It could be that AI can ad­di­tion­ally do some of the key an­i­ma­tor’s work, so that less keyframes

are pro­vided in some cases than you’d have to give a hu­man as­sis­tant (and one rea­son for this could be your abil­ity to quickly

get the AI to com­plete your work in 10-20 pos­si­ble ways, and choose the best op­tion, which is im­prac­ti­cal with a hu­man

as­sis­tant.) But the ba­sic role of the hu­man as a key an­i­ma­tor would re­main, and so the first thing to ex­plore is the ma­chine

tak­ing over the as­sis­tan­t’s role.

So I’m not say­ing that we can’t im­prove pro­duc­tiv­ity be­yond the machine as the as­sis­tant” arrange­ment, nor that we must limit our­selves to the tra­di­tional ap­pear­ance of hand-drawn an­i­ma­tion. I’m just say­ing that our con­ser­v­a­tive scope is

likely the right start­ing point, even if our fi­nal goals are more am­bi­tious - at least as long as we want the hu­man to

re­main the ac­tor.

What would the ma­chine do in an as­sis­tan­t’s role? Traditionally, as­sis­tants’ jobs in­clude:

* Coloring (“should” be triv­ial with a paint bucket tool, but sur­pris­ingly an­noy­ing around small gaps in the lines)

Our scope here is nar­rowed fur­ther by fo­cus­ing ex­clu­sively on in­be­tween­ing. There’s no deep rea­son for this be­yond hav­ing to start some­where, and in­be­tween­ing be­ing the most animation-y” as­sis­tan­t’s job, be­cause it’s about move­ment. So fo­cus­ing our search on in­be­tween­ing is most likely to give re­sults rel­e­vant to an­i­ma­tion and not just still” line art.

Finally, in this in­stall­ment, we’re go­ing to fo­cus on pa­pers which call them­selves AI for an­i­ma­tion

in­be­tween­ing” pa­pers. It’s not ob­vi­ous that any rel­e­vant killer tech­nique” has to come from a pa­per fo­cus­ing on this prob­lem ex­plic­itly. We could end up bor­row­ing ideas from pa­pers on video frame in­ter­po­la­tion, or video/​an­i­ma­tion gen­er­a­tion not de­signed for in­be­tween­ing, etc. In fact, I’m look­ing at some things like this. But again, let’s start some­where.

Before look­ing at pa­pers for the lat­est ideas, let’s check out Runway Frame Interpolation. Together with Stability AI and the CompVis group, Runway re­searchers were be­hind Stable Diffusion, and Runway is at the fore­front of de­ploy­ing gen­er­a­tive AI for video.

Let’s test frame in­ter­po­la­tion on a sneaky car­toony rab­bit se­quence. It’s good as a test se­quence be­cause it has both fast/​large and slower/​smaller move­ment (so both harder and eas­ier parts.) It also has both flat 2D body move­ment and 3D head ro­ta­tion - one might say too much ro­ta­tion… But ro­ta­tion is good to test be­cause it’s a big rea­son for do­ing full hand-drawn an­i­ma­tion. Absent ro­ta­tion, you can split your char­ac­ter into cut-out” parts, and an­i­mate it by mov­ing and stretch­ing these parts.

We throw away every sec­ond frame, ask Runway to in­ter­po­late the se­quence, and af­ter some con­ver­sions and a frame rate ad­just­ment (don’t ask), we get some­thing like this:

This tool def­i­nitely is­n’t cur­rently op­ti­mized for car­toony mo­tion. Here’s an ex­am­ple in­be­tween:

Now let’s try a sim­i­lar se­quence with a sneaky me in­stead of a sneaky rab­bit. Incidentally, this is one of sev­eral styles I’m in­ter­ested in - some­thing be­tween live ac­tion and Looney Tunes, with this self-por­trait tak­ing live ac­tion maybe 15% to­wards Looney Tunes:

Frame in­ter­po­la­tion looks some­what bet­ter here, but it’s still more mor­ph­ing than mov­ing from pose to pose:

While the Frame Interpolation tool cur­rently does­n’t work for this use case, I’d bet that Runway could solve the prob­lem quicker and bet­ter than most if they wanted to. Whether there’s a large enough mar­ket for this is an­other ques­tion, and it might de­pend on the ex­act de­f­i­n­i­tion of this.” Personally, I be­lieve that a lot of good things in life can­not be monetized”, a lot of art-re­lated things are in this un­for­tu­nate cat­e­gory, and I’m very pre­pared to in­vest time and ef­fort into this with­out clear, or even any prospects of mak­ing money.

In any case, we’ve got our test se­quences, and we’ve got our mo­ti­va­tion to look for bet­ter per­for­mance in re­cent pa­pers.

There’s a lot of work on AI for im­age pro­cess­ing/​com­puter vi­sion. It’s nat­ural to bor­row tech­niques from this deeply re­searched space and ap­ply them to line art rep­re­sented as raster im­ages.

There are a few pa­pers do­ing this; AFAIK the state of the art with this ap­proach is cur­rently Improving the Perceptual Quality of 2D Animation Interpolation (2022). Their EISAI GitHub repo points to a co­lab demo and a Docker im­age for run­ning lo­cally, which I did, and things ba­si­cally Just Worked.

That this can even hap­pen blows my mind. I re­mem­ber how things worked 25 years ago, when you rarely had the code pub­lished, and peo­ple im­ple­ment­ing com­puter vi­sion pa­pers would oc­ca­sion­ally swear that the pa­per is out­right ly­ing, be­cause the de­scribed al­go­rithms don’t do and could­n’t pos­si­bly do what the pa­per says.

The se­quence be­low shows just in­be­tweens pro­duced by EISAI. Meaning, frame N is pro­duced from the orig­i­nal frames N-1 and N+1; there’s not a sin­gle orig­i­nal frame here. So this se­quence is­n’t di­rectly com­pa­ra­ble to Runway’s out­put.

I could­n’t quite pro­duce the same out­put with Runway as with the pa­pers (don’t ask.) If you care, this se­quence is closer to be­ing com­pa­ra­ble to Runway’s, if not fully ap­ples to ap­ples:

If you look at in­di­vid­ual in­be­tweens, you’ll see that EISAI and Runway have sim­i­lar dif­fi­cul­ties - big changes be­tween frames, oc­clu­sion and de­for­ma­tion, and both do their best and worst in about the same places. One of the best in­be­tweens by EISAI:

One of the worst:

The in­be­tweens are pro­duced by for­ward-warp­ing based on bidi­rec­tional flow es­ti­ma­tion. Flow es­ti­ma­tion” means com­put­ing, per pixel or re­gion in the first keyframe, its most likely cor­re­spond­ing lo­ca­tion in the other keyframe - finding where it went to” in the other im­age (if you have two im­ages of mostly the same thing,” you can hope to find parts from one in the other.) Warping” means trans­form­ing pixel data - for ex­am­ple, scal­ing, trans­lat­ing and ro­tat­ing a re­gion. Forward-warping by bidi­rec­tional flow es­ti­ma­tion” means tak­ing re­gions from both keyframes and warp­ing them to put them where they be­long” in the in­be­tween - which is halfway be­tween a re­gion’s po­si­tion in the source im­age, and the po­si­tion in the other im­age that the flow es­ti­ma­tion says this re­gion cor­re­sponds to.

Warping by flow ex­plains the oc­ca­sional 3-4 arms and legs and 2 heads (it warps a left hand from both in­put im­ages into two far-away places in the out­put im­age, since the flow es­ti­ma­tor found a wrong match, in­stead of match­ing the hands to each other.) This also ex­plains empty space” patches of var­i­ous sizes in the oth­er­wise flat back­ground.

Notably, warp­ing by flow gives up” on cases of oc­clu­sion up front (I mean cases where some­thing is vis­i­ble in one frame and not in the other due to ro­ta­tion or any other rea­son.) If your prob­lem for­mu­la­tion is let’s find parts of one im­age in the other im­age, and warp each part to the mid­dle po­si­tion be­tween where it was in the first and where we found it in the sec­ond” - then the cor­rect an­swer to where did the oc­cluded part move?” is I don’t know; I can’t track some­thing that is­n’t there.”

When the op­ti­cal flow matches large parts” be­tween im­ages cor­rectly, you still have oc­ca­sional is­sues due to both im­ages be­ing warped into the re­sult, with ghosting” of de­tails of fin­gers or noses or what-not (meaning, you see two slightly dif­fer­ent draw­ings of a hand at roughly the same place, and you see one draw­ing through the other, as if that other draw­ing was a semi-trans­par­ent ghost”.) A dumb ques­tion com­ing to my mind is if this could be im­proved through brute force, by increasing the res­o­lu­tion of the im­age” / hav­ing a higher-resolution flow es­ti­ma­tion,” so you have a larger num­ber of smaller patches ca­pa­ble of rep­re­sent­ing the de­for­ma­tions of de­tails, be­cause each patch is tracked and warped sep­a­rately.

An in­ter­est­ing thing in this pa­per is the use of dis­tance

trans­form to create” tex­ture for con­vo­lu­tional neural net­works to work with for fea­ture ex­trac­tion. The dis­tance trans­form re­places every pixel value with the dis­tance from that pix­el’s co­or­di­nates to the clos­est black pixel. If you in­ter­pret dis­tances as black & white pixel val­ues, this gives texture” to your line art in a way. The pa­per cites Optical flow based line draw­ing frame in­ter­po­la­tion us­ing dis­tance trans­form to sup­port in­be­tween­ings” (2019) which also used dis­tance trans­form for this pur­pose.

If you’re deal­ing with 2D an­i­ma­tion and you’re bor­row­ing im­age pro­cess­ing/​com­puter vi­sion neural net­works (hyperparameters and maybe even pre­trained weights, as this pa­per does with a few lay­ers of ResNet), you will have the prob­lem of lack of tex­ture” - you have these large flat-color re­gions, and the out­put of every con­vo­lu­tion on each pixel within the re­gion is ob­vi­ously ex­actly the same. Distance trans­form gives some tex­ture for the con­vo­lu­tions to respond” to.

This amuses me in a machine learn­ing in­side joke” sort of way. But they told me that man­ual fea­ture en­gi­neer­ing

was over in the era of Deep Learning!” I mean, sure, a lot of it is over - you won’t see a pa­per on the next SIFT or HOG.” But, apart from the hyperparameters” (a name for, ba­si­cally, the en­tire net­work ar­chi­tec­ture) be­ing man­u­ally en­gi­neered, and the var­i­ous man­ual data aug­men­ta­tion and what-not, what’s Kornia, if not a tool for man­ual fea­ture en­gi­neer­ing in a dif­fer­en­tiable pro­gram­ming con­text”? And I’m not im­ply­ing that there’s any­thing wrong with it - quite the con­trary, my point is that peo­ple still do this be­cause it works, or at least makes some things work bet­ter.

Before we move on to other ap­proaches, let’s check how EISAI does on the rab­bit se­quence. I don’t care for the rab­bit se­quence; I’m self­ishly in­ter­ested in the me se­quence. But since un­like Runway, EISAI was trained on an­i­ma­tion data, it seems fair to feed it some­thing more like the train­ing data:

Both Runway and EISAI do worse on the rab­bit, which has more change in hands and ears and walks a bit faster. It seems that large move­ments, de­for­ma­tions and ro­ta­tions af­fect per­for­mance more than similarity to train­ing data,” or at least sim­i­lar­ity in a naive sense.

Instead of treat­ing the in­put as im­ages, you could work on a vec­tor rep­re­sen­ta­tion of the lines. AFAIK the most re­cent pa­per in this cat­e­gory is Deep Geometrized Cartoon Line Inbetweening (2023). Their AnimeInbet GitHub repo lets you re­pro­duce the pa­per’s re­sults. To run on your own data, you need to hack the code a bit (at least I did­n’t man­age with­out some code changes.) More im­por­tantly, you need to vec­tor­ize your in­put data some­how.

The pa­per does­n’t come with its own in­put draw­ing vec­tor­iza­tion sys­tem, and ar­guably should­n’t, since vec­tor draw­ing pro­grams ex­ist, and vec­tor­iz­ing raster draw­ings is a prob­lem in its own right and out­side the pa­per’s scope. The code in the pa­per has no trou­ble get­ting in­put data in a vec­tor rep­re­sen­ta­tion be­cause their line art dataset is pro­duced from their dataset of mov­ing 3D char­ac­ters, ren­dered with a toon shader” or what­ever the thing ren­der­ing lines in­stead of shaded sur­faces is called. And since the 2D points/​lines come from 3D ver­tices/​edges, you’re ba­si­cally pro­ject­ing a 3D vec­tor rep­re­sen­ta­tion into a 2D space and it’s still a vec­tor rep­re­sen­ta­tion.

What’s more, this data set pro­vides a kind of ground truth that you don’t get from 2D an­i­ma­tion data sets - namely,

de­tailed cor­re­spon­dence be­tween the points in both in­put frames and the ground truth in­be­tween frame. If your ground truth is a frame from an an­i­mated movie, you only know that this frame is the in­be­tween you ex­pect be­tween the pre­vi­ous frame and the next.” But here, you know where every 3D ver­tex ended up in every im­age!

This cor­re­spon­dence in­for­ma­tion is used at train­ing time - and omit­ted at in­fer­ence time, or it would be cheat­ing. So if you want to feed data into AnimeInbet, you only need to vec­tor­ize this data into points con­nected by straight lines, with­out wor­ry­ing about ver­tex cor­re­spon­dence. The pa­per it­self cites Virtual

Sketching, it­self a deep learn­ing based sys­tem, as the vec­tor­iza­tion tool they used for their own ex­per­i­ments in one of the ablation stud­ies” (I know it’s id­iomatic sci­en­tific lan­guage, but can I just say that I love this ex­pres­sion? Please don’t con­tribute to the pro­ject dur­ing the next month. We’re per­form­ing an ab­la­tion study of in­di­vid­ual pro­duc­tiv­ity. If the study proves suc­cess­ful, you shall be ab­lated from the com­pany by the end of the month.”)

There are com­ments in the AnimeInbet repo about is­sues us­ing Virtual Sketching; mine was that some lines par­tially dis­ap­peared (could be my fault for not us­ing it prop­erly.) I ended up writ­ing some ne­an­derthal-style im­age pro­cess­ing code skele­toniz­ing the raster lines, and then flood-fill­ing the skele­ton and con­nect­ing the points while flood-fill­ing. I’d ex­plain this at more length if it was more than a one-off hack; for what it’s worth, I think it’s rea­son­ably cor­rect for pre­sent pur­poses. (My testing” is that when I ren­der my ver­tices and the lines con­nect­ing them and eye­ball the re­sult, no ob­vi­ously stu­pid line con­nect­ing un­re­lated things ap­pears, and no big thing from the in­put raster im­age is clearly miss­ing.)

This hacky vectorization” code (might need more hack­ing to ac­tu­ally use) is in Animation Papers GitHub repo, to­gether with other code you might use to run AnimeInbet on your data.

The rab­bit is harder for AnimeInbet, sim­i­larly to the oth­ers. For ex­am­ple, the ears are com­pletely de­stroyed by the head turn, as usual:

The worst and the best in­be­tweens oc­cur in pretty much the same frames:

Visually no­table as­pects of AnimeInbet’s out­put com­pared to the pre­vi­ous sys­tems we’ve seen:

* AnimeInbet does­n’t blur lines. It might shred lines on oc­ca­sion, but you don’t blur

vec­tor lines like you blur pix­els. (You very much can put a bunch of garbage lines into the out­put, and AnimeInbet is

pretty good at not do­ing that, but this ca­pa­bil­ity be­longs to our next item. Here we’ll just note that raster-based

sys­tems did­n’t quite learn” to avoid line blur­ring, which this sys­tem avoids by de­sign.)

* AnimeInbet seems quite good at match­ing small de­tails and avoid­ing ghost­ing/​copy­ing the same thing twice from both

im­ages. This is not some­thing that can sal­vage bad in­be­tweens, but it makes good in­be­tweens bet­ter; in the one above,

the pants and the hands are ex­am­ples where small de­tail is matched bet­ter than in the raster sys­tems.

* For every part, AnimeInbet ei­ther finds a match or re­moves it from the out­put. The pa­per for­mu­lates

in­be­tween­ing as a graph match­ing prob­lem (where ver­tices are the nodes and the lines con­nect­ing them are edges.) Parts with­out a

match are marked as in­vis­i­ble. This does­n’t solve” oc­clu­sion or ro­ta­tion, but it tends to keep you from putting stuff into the

out­put that the an­i­ma­tor needs to erase and re­draw af­ter­wards. This makes good in­be­tweens mar­gin­ally bet­ter; for bad in­be­tweens,

it makes them less funny” but prob­a­bly not much more us­able (you get 2 legs in­stead of 4, but they’re of­ten not the right

legs; and you can still get a head with two fore­heads as in the bad in­be­tween above.)

AnimeInbet has a com­pre­hen­sive eval­u­a­tion of their sys­tem vs other sys­tems (EISAI and VFIformer as well as FILM and RIFE, video in­ter­po­la­tion rather than specif­i­cally an­i­ma­tion in­be­tween­ing sys­tems.) According to their method­ol­ogy (where they use their own test dataset), their sys­tem comes out ahead by a large mar­gin. In my ex­tremely small-scale and qual­i­ta­tive test­ing, I’d say that it looks bet­ter, too, though per­haps less dra­mat­i­cally.

Here we have deep learn­ing with a model and in­put data set tai­lored care­fully to the prob­lem - some­thing I think you won’t see as of­ten as pa­pers reusing one or sev­eral pre­trained net­works, and com­bin­ing them with var­i­ous adap­ta­tions to ap­ply to the prob­lem at hand. My emo­tional re­ac­tion to this ap­proach ap­pear­ing to do bet­ter than ideas bor­rowed from general im­age/​video AI re­search” is mixed.

I like being right” (well, vaguely) about AI not be­ing general ar­ti­fi­cial in­tel­li­gence” but a set of tech­niques that you need to ap­ply care­fully to build a sys­tem for your needs, in­stead of just throw­ing data into some gi­ant gen­eral-pur­pose black box - this is some­thing I like go­ing on about, maybe more than I should given my level of un­der­stand­ing. As a prospec­tive user/​im­ple­menter look­ing for the next break­through pa­per,” how­ever, it would be bet­ter for me if ideas bor­rowed from general video re­search” worked great, be­cause there’s so many of them com­pared to the vol­ume of animation-focused re­search.”

I mean, Disney al­ready fired its hand-drawn an­i­ma­tion de­part­ment years ago. If the medium is to be re­vived (and peo­ple even car­ing about it aren’t get­ting any younger), it’s less likely to hap­pen through di­rect in­vest­ment into an­i­ma­tion than as a byprod­uct of other, more prof­itable things. I guess we’ll see how it goes.

No fu­ture im­prove­ment of the tech­niques in both pa­pers can pos­si­bly take care of all of in­be­tween­ing,” be­cause oc­clu­sion and ro­ta­tion hap­pen a lot, and do not fit these pa­pers’ ba­sic ap­proach of match­ing 2D fea­tures in the in­put frames. And even the best in­be­tweens aren’t quite us­able as is. But they could be used with some edit­ing, and it could be eas­ier to edit them than draw the whole thing from scratch.

An en­cour­ag­ing ob­ser­va­tion is that ma­chines strug­gle with big changes and peo­ple strug­gle with small changes, so they

can com­ple­ment each other well. A hu­man is bet­ter at (and less bored by) draw­ing an in­be­tween be­tween two keyframes which look very dif­fer­ent than draw­ing some­thing very close to both in­put frames and putting every line at ju­u­u­u­ust the right place. If ma­chines can help han­dle the lat­ter kind of work, even with some edit­ing re­quired, that’s great!

It’s very in­ter­est­ing to look into ap­proaches that can in fact han­dle more change be­tween in­put frames. For ex­am­ple, check out the mid­dle frame be­low, gen­er­ated from the frames on its left and right:

This is from Explorative Inbetweening of Time and Space (2024); they say the code is com­ing soon. It does have some prob­lems with oc­clu­sion (look at the right arm in the mid­dle im­age.) But it seems to only strug­gle when show­ing some­thing that is oc­cluded in both in­put frames (for ex­am­ple, the right leg is fine, though it’s largely oc­cluded in the im­age on the left.) This is a big im­prove­ment over what we’ve seen above, or right be­low (this is one frame of Runway’s out­put, where one right leg slowly merges into the left leg, while an­other right leg is grow­ing):

But what’s even more im­pres­sive - ex­tremely im­pres­sive - is that the sys­tem de­cided that the body would go up be­fore go­ing back down be­tween these two poses! (Which is why it’s hav­ing trou­ble with the right arm in the first place! A fea­ture match­ing sys­tem would­n’t have this prob­lem, be­cause it would­n’t re­al­ize that in the mid­dle po­si­tion, the body would go up, and the right arm would have to be some­where. Struggling with things not vis­i­ble in ei­ther in­put keyframe is a good prob­lem to have - it’s ev­i­dence of know­ing these things ex­ist, which demon­strates quite the ca­pa­bil­i­ties!)

This sys­tem clearly learned a lot about three-di­men­sional real-world move­ment be­hind the 2D im­ages it’s asked to in­ter­po­late be­tween. Let’s call ap­proaches go­ing in this di­rec­tion 3D mo­tion re­con­struc­tion” tech­niques (and I apol­o­gize if there’s bet­ter, stan­dard ter­mi­nol­ogy / tax­on­omy; I’d use it if I knew it.)

My point here, be­yond ea­gerly wait­ing for the code in this pa­per, is that fea­ture match­ing tech­niques might re­main in­ter­est­ing in the long term, pre­cisely be­cause they don’t un­der­stand what’s go­ing on in the scene.” Sure, they clearly don’t learn how a fig­ure moves or looks like.” But this gives some hope that what they can do - han­dling small changes - will work on more kinds of in­puts. Meaning, a sys­tem that learned hu­man move­ment” might be less use­ful for an oc­to­pus se­quence than a sys­tem that learned to match patches of pix­els, or graphs of points con­nected by lines.” So falling back on 2D fea­ture match­ing could re­main use­ful for a long time, even once 3D mo­tion re­con­struc­tion works great on the kinds of char­ac­ters it was trained on.

...

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Tips on how to structure your home directory

Someone wrote me an email and asked if I could share some tips on how to struc­ture the $HOME di­rec­tory, so here we go.

Structuring or or­ga­niz­ing di­rec­to­ries is not much dif­fer­ent from struc­tur­ing or or­ga­niz­ing other stuff and it re­ally comes down to what makes the most sense to you - at least as long as you’re only deal­ing with your own di­rec­to­ries. As soon as you’re deal­ing with an or­ga­ni­za­tion, things can very quickly get out of hand.

The main pur­pose be­hind any kind of or­ga­niz­ing is ef­fi­ciency. That re­ally is the key­word. You need to be able to eas­ily and quickly find what you’re look­ing for and just as eas­ily and quickly be able to store what needs to be stored.

Over the years I have changed my di­rec­tory struc­ture for my home di­rec­tory a cou­ple of times, but not so for about the last 10+ years be­cause I have set­tled on some­thing that works re­ally well for me.

I don’t like clut­ter and I try to keep things sim­ple. If I need some kind of rule book in or­der to re­mem­ber how to store my files in my home di­rec­tory, then this is a clear sign that some­thing has gone wrong.

In my home di­rec­tory I have all the ba­sic hid­den stuff which is a part of any mod­ern Unix op­er­at­ing sys­tem such as .config, .aliases, .profile, .gnupg, .mozilla, etc. Though I would pre­fer that all ap­pli­ca­tions would re­spect the XDG_CONFIG_HOME, which de­faults to $HOME/.config, I don’t mess with that and gen­er­ally don’t care too much about that.

In the past I kept my $HOME in Git - the right way ;), which is a re­ally great way to or­ga­nize dot­files. Today I still put all my dot­files in Git be­cause I like to keep a his­tory of changes, but I only leave those dot­files in place which work iden­ti­cally across the dif­fer­ent sys­tems I use. The setup spe­cific dot­files is kept in a dotfiles” di­rec­tory and I then use sym­links (more about that in a lit­tle while).

Regarding nor­mal files and di­rec­to­ries I pri­mar­ily use two meth­ods of or­ga­niz­ing, namely category” and dates”.

This is my ba­sic di­rec­tory struc­ture:

bin

data

edata

mnt

usr/​dot­files

Besides from the above, I just leave the Desktop and Downloads di­rec­to­ries, which dif­fer­ent ap­pli­ca­tions seem to want to shove down the throat of every­body. In the past I fought” against those, be­cause I gen­er­ally don’t use them and I don’t like them, but life is just too short to mess with crap like that.

Update 2023-09-04: You can set di­rec­to­ries such as Desktop, Downloads and oth­ers with the user-dirs.dirs - set­tings for XDG user dirs, which most ap­pli­ca­tions should re­spect (thanks Hugo for point­ing this out!)

In the bin di­rec­tory I keep my shell scripts and per­sonal bi­nary ex­e­cuta­bles (not stuff in­stalled via the pack­age man­ager).

The mnt di­rec­tory I use for dif­fer­ent mount points, like when I mount an SD card, a USB disk, some of the shared stor­age I use in my home­lab.

It looks some­thing like this:

mnt

\foo

\bar

\baz

I never auto mount, but gen­er­ally use shell scripts for mount­ing. So if I have a USB disk I call foo”, I have a shell script called mfoo. It does­n’t mat­ter how the foo” disk gets rec­og­nized by the sys­tem, the shell script will make sure that the disk gets mounted at mnt/​foo each time, and if the disk is en­crypted, it will prompt me for the passphrase, if I don’t use a key.

The usr/​dot­files di­rec­tory is kept in Git to­gether with generic dot­files that work iden­ti­cally across all sys­tems, like .aliases. I use sym­links to the rel­e­vant files in the dot­files di­rec­tory. It looks some­thing like this:

$ ls -l ~/usr/dotfiles/config/i3

freebsd-con­fig

linux-con­fig

$ ls -l ~/.config/i3

con­fig -> /home/foo/usr/dotfiles/config/i3/linux-config

linux-con­fig is then a spe­cific con­fig­u­ra­tion file for i3 which I only use on my Linux sys­tems. This might be be­cause the short­cut I use to run Firefox, starts Firefox in a AppArmor con­trolled Firejail, which does­n’t ex­ist on FreeBSD. On FreeBSD I might use Capsicum to get a sim­i­lar ex­pe­ri­ence. Just as an ex­am­ple.

I have a cou­ple of other sub­di­rec­to­ries in the $HOME/usr di­rec­tory be­sides the dot­files di­rec­tory, but those are not re­ally rel­e­vant to men­tion in de­tail for this ar­ti­cle (a di­rec­tory for some out­dated shell scripts, some wall­pa­pers, etc.)

NOTE: Configuration files (dotfiles) can be man­aged in many dif­fer­ent ways. I have changed my ap­proach a cou­ple of times through­out the years. My pre­ferred method is to keep my $HOME in Git. If you only run a sin­gle sys­tem or sim­i­lar sys­tems I can highly rec­om­mend the method I de­scribe in the tu­to­r­ial I have linked to.

But re­mem­ber this, don’t just fol­low what other peo­ple tell you to do, find the way that makes you the most pro­duc­tive, the way that is best wired to fit your brain, your way of think­ing” and then sim­ply change that if you later find a more pro­duc­tive way.

The data and edata di­rec­to­ries are the two main di­rec­to­ries where I keep all my stuff. These two di­rec­to­ries are ZFS datasets that run on a mir­rored pool of disks that are sep­a­rate from my root in­stal­la­tion. I run both FreeBSD and sev­eral dif­fer­ent Linux dis­tri­b­u­tions on my main work­sta­tion and these each run on their own set of disks.

All of this could be setup in other ways too, but I pre­fer this setup. I can eas­ily mount both data and edata from both FreeBSD and Linux.

The dif­fer­ence be­tween data and edata is that edata is a ZFS na­tive en­crypted dataset.

By uti­liz­ing ZFS I reg­u­larly use snap­shots and ZFS send and re­ceive for easy backup to net­work stor­age. This can be done even with­out de­crypt­ing the en­crypted dataset.

You could ask what the point is of hav­ing both an en­cryptet dataset and an un­en­cryptet dataset, why not just put every­thing into the en­cryptet dataset?

The fact is that I would rather not have any­thing en­cryptet at all. Encryption is great for pri­vacy, but it is an ab­solute hor­ri­ble layer of com­plex­ity to put on top of an al­ready com­plex layer of a filesys­tem and ZFS en­cryp­tion is not with­out its bugs, see is­sues 13533 and 14330.

TIP: I highly rec­om­mend that you ALWAYS backup all your im­por­tant data to mul­ti­ple dif­fer­ent stor­age so­lu­tions and lo­ca­tions - it’s okay to be para­noid about im­por­tant data.

Actually, you SHOULD be para­noid about im­por­tant data. I learned this the re­ally hard way - a long time ago - when I had just fin­ished writ­ing a 200+ A4 pages book and then lost every­thing be­cause of a silly mis­take and had to start all over and write the book again!

It is im­pos­si­ble to de­scribe that very spe­cial feel­ing that arises when you have just re­al­ized what just hap­pened! Noooooooooooooo! Pleeeeeeaseeeeee NOOOOOOOOOOO! (utter de­spair and dis­be­lief - LOL).

So, to­day I not only use ZFS send and re­ceive, but I also copy data to other filesys­tems all to­gether, us­ing rsync. For en­cryp­tion I uti­lize both ZFS na­tive en­cryp­tion, GELI (for my main FreeBSD root disks) and LUKS (for my main Linux root disks) and I also not only fol­low the 3-2-1 backup rule, but add fur­ther copies to mul­ti­ple sys­tems. That way, even if some bug is found that might cause a prob­lem for me, I have a high de­gree of be­ing able to get my files with­out hav­ing to mess with the prob­lem.

I do NOT use cloud stor­age for any­thing im­por­tant. I rather keep lo­cal copies at places like fam­ily, friends or in a safety de­posit box (unfortunately, safety de­posit boxes are cur­rently be­ing re­moved from the banks in Denmark).

In the data di­rec­tory I have a few sub­di­rec­to­ries:

books

notes

source

The books di­rec­tory con­tains books I have writ­ten or I am work­ing on.

The source di­rec­tory con­tains source code for var­i­ous pro­jects I work on.

The notes di­rec­tory con­tains a huge amount of per­sonal notes on every­thing from health to pol­i­tics to com­puter re­lated sub­jects. I write every­thing in pure text, mainly in Markdown or just with­out any spe­cial markup. Everything is struc­tured ac­cord­ing to cat­e­gory or sub­ject and it looks like this (short ver­sion):

data/​notes/

as­tron­omy

busi­ness

elec­tron­ics

health

it

lan­guage

Each main sub­ject also has a sub­di­rec­tory called files which I use for stuff I find on­line re­lated to the sub­ject. Files in the files di­rec­tory can be im­ages, text, au­dio and video. If I only have a few files, I just dump them all in the files di­rec­tory, but if I have a lot, I or­ga­nize them fur­ther by putting them in the rel­e­vant cat­e­gories.

Within each cat­e­gory of di­rec­tory I might also keep a hid­den sub­di­rec­tory called .outdated. I use this hid­den di­rec­tory to put stuff away that is, well, out­dated, but might still come in handy.

It then looks some­thing like this:

$ tree

└── data

└── notes

└── it

└── op­er­at­ing-sys­tems

├── freebsd

│   ├── .outdated

│   ├── files

│   │   ├── au­dio

│   │   ├── im­ages

│   │   ├── text

│   │   │   └── why-we-mi­grated-away-from-y-at-foo.pdf

│   │   └── video

│   │   └── how-we-setup-y-at-z.mp4

│   ├── how-to-do-x.md

│   └── how-to-setup-y.md

├── linux

└── openbsd

I al­ways keep an ex­ported shell vari­able that con­tains the lo­ca­tion of my notes. That way I can eas­ily link to any other doc­u­ment or ex­ter­nal file from within my notes and use Vim to open the file (if it’s a text doc­u­ment) by press­ing gf or use Vim’s build in abil­ity to ex­e­cute a shell com­mand from within the doc­u­ment. I use that to view PDF files or play a video, etc.

In my notes I might have a Markdown link to a PDF file which looks like this:

This is the [foo doc­u­ment]($NOTES/​it/​op­er­at­ing-sys­tems/​freebsd/​files/​text/​foo.pdf) rel­e­vant for in­for­ma­tion about foo.

When you have setup a de­fault ap­pli­ca­tion for read­ing PDF files, then from within Vim you can just place the cur­sor on the file­name and then press gx and Vim will open up the PDF file in the rel­e­vant PDF reader. Or you can copy and paste the path to the file and then open it with your PDF reader by typ­ing ! from within Vim (I gen­er­ally use MuPDF or za­thura for read­ing PDF doc­u­ments):

:!mupdf $NOTES/it/operating-systems/freebsd/files/text/foo.pdf

This works for other ap­pli­ca­tions as well, such as open­ing video with mpv or im­ages with some­thing like feh.

NOTE: Hyphen vs un­der­score in file­names and di­rec­tory names?

Originally, when I stopped us­ing Windows back in about 1998, I was used to us­ing spaces be­tween words in file­names and di­rec­to­ries. As I pro­gressed into the world of Linux and BSD, I changed all spaces to un­der­scores, but since I have done (and still do) a lot of web de­vel­op­ment I even­tu­ally set­tled on hy­phens. I not only think it looks bet­ter, but the fact is that search en­gines in­ter­pret hy­phens in file and di­rec­tory names as spaces be­tween words. Underscores are usu­ally not rec­og­nized, and as such, their pres­ence can neg­a­tively af­fect search en­gine op­ti­miza­tion. Even though files in my home di­rec­tory are my pri­vate files and not some­thing I put out on the web, I have just set­tled on us­ing hy­phens every­where.

Filename foo_bar_baz” be­comes foobarbaz” on a search en­gine, whereas foo-bar-baz” be­comes foo bar baz”.

As men­tioned, I also keep an en­crypted di­rec­tory called edata. I do that be­cause I be­lieve that it’s im­por­tant to en­crypt pri­vate stuff in case your com­puter gets stolen.

TIP: Remember that if you use en­cryp­tion for any­thing which other fam­ily mem­bers might need to be able to ac­cess in case you pass away, you need to make sure that they know how to do that!

The edata di­rec­tory is or­ga­nized in a sim­i­lar fash­ion with categories” be­ing the main struc­ture.

doc­u­ments

\letters

\foo

\bar

\receipts

\media

\family

\audio

...

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