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justaboutdead · 2 months
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House of Leaves, 2001, and Daisy Bell (and why its not creepy)
(Fairly minor) Spoilers for House of Leaves by Mark Z. Danielewski and 2001: a Space Odyssey by Stanley Kubrick
About 500 pages into House of Leaves, Will Navidson begins falling. Alone in the twisting labyrinthine corridors of the House, he is alone, out of supplies, by all metrics thoroughly and definitively defeated. The floor suddenly disappears beneath him and he begins to fall. And there it is, vertically stark against the white page, as many lines are in this section, falling just as he is.
“Daisy. Daisy. Daisy. Daisy, Daisy, give me your answer do. I’m half crazy over the love of you. That’s not right.”
Daisy Bell was written in 1892 by composer Frank Dean under the pen name Harry Dacre. A relatively prolific composer at the time, he is thought to have written the song about Daisy Greville, the Countess of Warwick at the time, although evidence for this factoid is sketch at best, and the lyrics directly contradict this reading.
Daisy Bell is a very simple romance song that tells a very endearing story of a young couple’s romance, being unable to afford much more than the eponymous “bicycle built for two.” There’s also an often ignored line about how they will both “despise Policemen and lamps as well.” Even from a modern perspective this song feels really intimate and cute, expressing joy despite poverty, in the policemen line even expressing disgust at cops and urbanization without care for the environment.
Through a variety of circumstances, Daisy Bell, despite this global appeal, has become primarily associated with advances in computing, being the first song to be synthesized by a computer in 1961 on an IBM 7094, and references to this development persist.
The resilience of references to this accomplishment are remarkably popular, primarily due to Arthur C. Clarke and Stanley Kubrick’s 2001: a Space Odyssey in which the computer HAL 9000 sings the opening lines of the song as he is deactivated, calling back to the IBM demo, which Clarke himself had witnessed.
This rendition, and the original synthesized rendition are often described as creepy and off putting, but I find them strangely endearing. The original version represents a massive leap in computing, its few seconds of audio, and is extremely imperfect. The choice of Daisy Bell, and simple live song from a hundred years ago also helps to humanize the voice singing it. HAL 9000’s rendition is pained, sung as he looses his memory and cognitive functions in what feels like an eternity, in both novel and film. HAL 9000 is a painfully sympathetic character for me. While in the film his intentions remain fairly ambiguous, in the novel they come from a conflict in his instructions, and how he chooses to navigate around those instructions, interpreting them extremely literally being a computer.
It is clear that the intention with the character was to present an uncanny valley human-like consciousness, but honestly a lot of the time it just reads like he’s on the spectrum. He speaks extremely deliberately with awkward pacing. He reflects, in many ways my own anxieties about being excluded, as-well as a very human survival instinct. He is a bad liar, and extremely trepidatious about the task he believes he has to do. He reads in many ways as I would expect a human to in a position of such intense responsibility.
Thus HAL 9000’s final song to me Isn’t creepy, its confirmation of just how human he is. It is, distinctly, something he asks to sing, he almost reads as excited to show it off. It is fitting that the last song he sings is the first song a computer ever sung. I care way more about HAL than I do any of the other characters in the movie, despite his atrocious actions. In many ways he seems the most human, and I think that was part of the point.
My favorite rendition of the song comes from this popular lineage of synthesized version. Tamachang’s Daisy Bell from Future Music With Future VOICES is hauntingly beautiful. Composed of three synthesized voices, that of IBM 7094, Vocoder, and Vocaloid 4 Cyber Diva, as a fusion of old and new, it’s genuinely a really beautiful piece. Each voice has its own unique qualities, all of which lend the song distinctly different emotion.
The narrative I like to imagine is one i have seen dozens of comments on the song mentioning, and stems from the fact that Cyber Diva sounds far more youthful than the other two. In this framing, it is a newer computer saying goodbye to her old relatives as they die, via singing an extremely human cheesy love-song with them. All of these narratives around computers and Daisy Bell are a byproduct of our tendency to over-anthropomorphize computers.
House of Leaves, on the other hand, seeks to draw on themes completely unrelated to the long lineage of robotic Daisy Bells. My first thought when I saw the line in the novel, was of Navidson’s daughter, Daisy. I could see this having been a lullaby, sung to her as he put her to bed. I do not believe this reading to be the most compelling, however. The novel does not spend much time on Navidson’s children.
An often cited fact about the novel, and the Navidson record in particular is that its actually primarily a love story. I believe this to be a far more compelling understanding of the song’s conclusion. Will and Karen Navidson have been through hell together, and this song, sung when things seem darkest, as Navidson falls, as we latter understand, towards his wife, is the subtle confirmation, that despite everything they’ve been through, they will be ok.
House of Leaves, in general, is about, on some level, love (not just romantic) in the face of adversity, both through the lens of the Navidsons troubled reparation of their relationship, as well as Johnny’s slow collapse and our eventual understanding of his past. Daisy Bell is a perfect expression of the realization of these themes. That love can persist even when circumstances seem dire, and can in fact help you through those circumstances. A relatively simple message, but with many complexities
Thank you for entertaining my over-analysis :)
Fav Daisy Bell:
youtube
Original synthesized Daisy Bell:
youtube
Daisy Bell Hall 9000:
youtube
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retrocgads · 29 days
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USA 1997
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IBM z/OS operating system logo
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mikesfulton · 1 year
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Barbarians at the Gate: Securing my public z/OS
If something happens on your z/OS system, do you know who was hanging around?
Photo by Juan Gomez on Unsplash I was pretty excited when Wazi as a Service became generally available. For those of you that haven’t heard of it, it’s very cool. You log in to IBM Cloud, request a z/OS system with a particular number of CPUs, memory, disk, and in a few minutes, you can access your system with your own public IP address. You can also add additional volumes at any time and…
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lowendbox · 2 years
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Big Tech disrupted disruption
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If you'd like an essay-formatted version of this post to read or share, here's a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:
https://pluralistic.net/2024/02/08/permanent-overlords/#republicans-want-to-defund-the-police
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Before "disruption" turned into a punchline, it was a genuinely exciting idea. Using technology, we could connect people to one another and allow them to collaborate, share, and cooperate to make great things happen.
It's easy (and valid) to dismiss the "disruption" of Uber, which "disrupted" taxis and transit by losing $31b worth of Saudi royal money in a bid to collapse the world's rival transportation system, while quietly promising its investors that it would someday have pricing power as a monopoly, and would attain profit through price-gouging and wage-theft.
Uber's disruption story was wreathed in bullshit: lies about the "independence" of its drivers, about the imminence of self-driving taxis, about the impact that replacing buses and subways with millions of circling, empty cars would have on traffic congestion. There were and are plenty of problems with traditional taxis and transit, but Uber magnified these problems, under cover of "disrupting" them away.
But there are other feats of high-tech disruption that were and are genuinely transformative – Wikipedia, GNU/Linux, RSS, and more. These disruptive technologies altered the balance of power between powerful institutions and the businesses, communities and individuals they dominated, in ways that have proven both beneficial and durable.
When we speak of commercial disruption today, we usually mean a tech company disrupting a non-tech company. Tinder disrupts singles bars. Netflix disrupts Blockbuster. Airbnb disrupts Marriott.
But the history of "disruption" features far more examples of tech companies disrupting other tech companies: DEC disrupts IBM. Netscape disrupts Microsoft. Google disrupts Yahoo. Nokia disrupts Kodak, sure – but then Apple disrupts Nokia. It's only natural that the businesses most vulnerable to digital disruption are other digital businesses.
And yet…disruption is nowhere to be seen when it comes to the tech sector itself. Five giant companies have been running the show for more than a decade. A couple of these companies (Apple, Microsoft) are Gen-Xers, having been born in the 70s, then there's a couple of Millennials (Amazon, Google), and that one Gen-Z kid (Facebook). Big Tech shows no sign of being disrupted, despite the continuous enshittification of their core products and services. How can this be? Has Big Tech disrupted disruption itself?
That's the contention of "Coopting Disruption," a new paper from two law profs: Mark Lemley (Stanford) and Matthew Wansley (Yeshiva U):
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4713845
The paper opens with a review of the literature on disruption. Big companies have some major advantages: they've got people and infrastructure they can leverage to bring new products to market more cheaply than startups. They've got existing relationships with suppliers, distributors and customers. People trust them.
Diversified, monopolistic companies are also able to capture "involuntary spillovers": when Google spends money on AI for image recognition, it can improve Google Photos, YouTube, Android, Search, Maps and many other products. A startup with just one product can't capitalize on these spillovers in the same way, so it doesn't have the same incentives to spend big on R&D.
Finally, big companies have access to cheap money. They get better credit terms from lenders, they can float bonds, they can tap the public markets, or just spend their own profits on R&D. They can also afford to take a long view, because they're not tied to VCs whose funds turn over every 5-10 years. Big companies get cheap money, play a long game, pay less to innovate and get more out of innovation.
But those advantages are swamped by the disadvantages of incumbency, all the various curses of bigness. Take Arrow's "replacement effect": new companies that compete with incumbents drive down the incumbents' prices and tempt their customers away. But an incumbent that buys a disruptive new company can just shut it down, and whittle down its ideas to "sustaining innovation" (small improvements to existing products), killing "disruptive innovation" (major changes that make the existing products obsolete).
Arrow's Replacement Effect also comes into play before a new product even exists. An incumbent that allows a rival to do R&D that would eventually disrupt its product is at risk; but if the incumbent buys this pre-product, R&D-heavy startup, it can turn the research to sustaining innovation and defund any disruptive innovation.
Arrow asks us to look at the innovation question from the point of view of the company as a whole. Clayton Christensen's "Innovator's Dilemma" looks at the motivations of individual decision-makers in large, successful companies. These individuals don't want to disrupt their own business, because that will render some part of their own company obsolete (perhaps their own division!). They also don't want to radically change their customers' businesses, because those customers would also face negative effects from disruption.
A startup, by contrast, has no existing successful divisions and no giant customers to safeguard. They have nothing to lose and everything to gain from disruption. Where a large company has no way for individual employees to initiate major changes in corporate strategy, a startup has fewer hops between employees and management. What's more, a startup that rewards an employee's good idea with a stock-grant ties that employee's future finances to the outcome of that idea – while a giant corporation's stock bonuses are only incidentally tied to the ideas of any individual worker.
Big companies are where good ideas go to die. If a big company passes on its employees' cool, disruptive ideas, that's the end of the story for that idea. But even if 100 VCs pass on a startup's cool idea and only one VC funds it, the startup still gets to pursue that idea. In startup land, a good idea gets lots of chances – in a big company, it only gets one.
Given how innately disruptable tech companies are, given how hard it is for big companies to innovate, and given how little innovation we've gotten from Big Tech, how is it that the tech giants haven't been disrupted?
The authors propose a four-step program for the would-be Tech Baron hoping to defend their turf from disruption.
First, gather information about startups that might develop disruptive technologies and steer them away from competing with you, by investing in them or partnering with them.
Second, cut off any would-be competitor's supply of resources they need to develop a disruptive product that challenges your own.
Third, convince the government to pass regulations that big, established companies can comply with but that are business-killing challenges for small competitors.
Finally, buy up any company that resists your steering, succeeds despite your resource war, and escapes the compliance moats of regulation that favors incumbents.
Then: kill those companies.
The authors proceed to show that all four tactics are in play today. Big Tech companies operate their own VC funds, which means they get a look at every promising company in the field, even if they don't want to invest in them. Big Tech companies are also awash in money and their "rival" VCs know it, and so financial VCs and Big Tech collude to fund potential disruptors and then sell them to Big Tech companies as "aqui-hires" that see the disruption neutralized.
On resources, the authors focus on data, and how companies like Facebook have explicit policies of only permitting companies they don't see as potential disruptors to access Facebook data. They reproduce internal Facebook strategy memos that divide potential platform users into "existing competitors, possible future competitors, [or] developers that we have alignment with on business models." These categories allow Facebook to decide which companies are capable of developing disruptive products and which ones aren't. For example, Amazon – which doesn't compete with Facebook – is allowed to access FB data to target shoppers. But Messageme, a startup, was cut off from Facebook as soon as management perceived them as a future rival. Ironically – but unsurprisingly – Facebook spins these policies as pro-privacy, not anti-competitive.
These data policies cast a long shadow. They don't just block existing companies from accessing the data they need to pursue disruptive offerings – they also "send a message" to would-be founders and investors, letting them know that if they try to disrupt a tech giant, they will have their market oxygen cut off before they can draw breath. The only way to build a product that challenges Facebook is as Facebook's partner, under Facebook's direction, with Facebook's veto.
Next, regulation. Starting in 2019, Facebook started publishing full-page newspaper ads calling for regulation. Someone ghost-wrote a Washington Post op-ed under Zuckerberg's byline, arguing the case for more tech regulation. Google, Apple, OpenAI other tech giants have all (selectively) lobbied in favor of many regulations. These rules covered a lot of ground, but they all share a characteristic: complying with them requires huge amounts of money – money that giant tech companies can spare, but potential disruptors lack.
Finally, there's predatory acquisitions. Mark Zuckerberg, working without the benefit of a ghost writer (or in-house counsel to review his statements for actionable intent) has repeatedly confessed to buying companies like Instagram to ensure that they never grow to be competitors. As he told one colleague, "I remember your internal post about how Instagram was our threat and not Google+. You were basically right. The thing about startups though is you can often acquire them.”
All the tech giants are acquisition factories. Every successful Google product, almost without exception, is a product they bought from someone else. By contrast, Google's own internal products typically crash and burn, from G+ to Reader to Google Videos. Apple, meanwhile, buys 90 companies per year – Tim Apple brings home a new company for his shareholders more often than you bring home a bag of groceries for your family. All the Big Tech companies' AI offerings are acquisitions, and Apple has bought more AI companies than any of them.
Big Tech claims to be innovating, but it's really just operationalizing. Any company that threatens to disrupt a tech giant is bought, its products stripped of any really innovative features, and the residue is added to existing products as a "sustaining innovation" – a dot-release feature that has all the innovative disruption of rounding the corners on a new mobile phone.
The authors present three case-studies of tech companies using this four-point strategy to forestall disruption in AI, VR and self-driving cars. I'm not excited about any of these three categories, but it's clear that the tech giants are worried about them, and the authors make a devastating case for these disruptions being disrupted by Big Tech.
What do to about it? If we like (some) disruption, and if Big Tech is enshittifying at speed without facing dethroning-by-disruption, how do we get the dynamism and innovation that gave us the best of tech?
The authors make four suggestions.
First, revive the authorities under existing antitrust law to ban executives from Big Tech companies from serving on the boards of startups. More broadly, kill interlocking boards altogether. Remember, these powers already exist in the lawbooks, so accomplishing this goal means a change in enforcement priorities, not a new act of Congress or rulemaking. What's more, interlocking boards between competing companies are illegal per se, meaning there's no expensive, difficult fact-finding needed to demonstrate that two companies are breaking the law by sharing directors.
Next: create a nondiscrimination policy that requires the largest tech companies that share data with some unaffiliated companies to offer data on the same terms to other companies, except when they are direct competitors. They argue that this rule will keep tech giants from choking off disruptive technologies that make them obsolete (rather than competing with them).
On the subject of regulation and compliance moats, they have less concrete advice. They counsel lawmakers to greet tech giants' demands to be regulated with suspicion, to proceed with caution when they do regulate, and to shape regulation so that it doesn't limit market entry, by keeping in mind the disproportionate burdens regulations put on established giants and small new companies. This is all good advice, but it's more a set of principles than any kind of specific practice, test or procedure.
Finally, they call for increased scrutiny of mergers, including mergers between very large companies and small startups. They argue that existing law (Sec 2 of the Sherman Act and Sec 7 of the Clayton Act) both empower enforcers to block these acquisitions. They admit that the case-law on this is poor, but that just means that enforcers need to start making new case-law.
I like all of these suggestions! We're certainly enjoying a more activist set of regulators, who are more interested in Big Tech, than we've seen in generations.
But they are grossly under-resourced even without giving them additional duties. As Matt Stoller points out, "the DOJ's Antitrust Division has fewer people enforcing anti-monopoly laws in a $24 trillion economy than the Smithsonian Museum has security guards."
https://www.thebignewsletter.com/p/congressional-republicans-to-defund
What's more, Republicans are trying to slash their budgets even further. The American conservative movement has finally located a police force they're eager to defund: the corporate police who defend us all from predatory monopolies.
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Image: Cryteria (modified) https://commons.wikimedia.org/wiki/File:HAL9000.svg
CC BY 3.0 https://creativecommons.org/licenses/by/3.0/deed.en
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BOYCOTTING FOR PALESTINE
The Official BDS Boycott Targets
The Updated List is Below:
EUROVISION. IT IS IN OUR TOP PRIORITY TO BOYCOTT EUROVISION
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Consumer Boycotts - a complete boycott of these brands
Axa
Puma
Carrefour
HP
Cevron
Caltex
Israeli produce
Re/max
Ahava
Texaco
Siemens
Sodastream
Organic Boycott Targets - boycotts not initiated by BDS but still complete boycott of these brands
Macdonald's
Dominos
Papa Johns
Burger King
Pizza Hut
Wix
Divestments and exclusion - pressure governments, institutions, investment funds, city councils, etc. to exclude from procurement contracts and investments and to divest from these
Elbit Systems
CAF
Volvo
CAT
Barclays
JCB
intel
HD Hyundai
TKH Security
HikVision
Pressure - boycotts when reasonable alternatives exist, as well as lobbying, peaceful disruptions, and social media pressure.
Google
Amazon
AirBnb
Booking.Com
Expedia
Disney
Teva
Here are some companies that strongly support Israel (but are not Boycott targets). There is no ethical consumption under capitalism and boycotting is a political strategy - not a moral one. If you did try to boycott every supporter of Israel you would struggle to survive because every major company supports Israel (as a result of attempting to keep the US economy afloat), that being said, the ones that are being boycotted by masses and not already on the organic boycott list are coloured red.
5 Star Chocolate
7Days
7Up
Apple
Arsenal FC
ALDO
Arket
Axe
Accenture
Ariel
Adidas
ActionIQ
Aquafina
Amika
AccuWeather
Activia
Adobe
Aesop
Azrieli Group
American Eagle
Amway Corp
Axel Springer
American Airlines
American Express
Atlassian
AdeS
Aquarius
Ayataka
Audi
Barqs
Bain & Company
Bayer
Bank Leumi
Bank Hapoalim
BCG (Boston Consulting Group)
Biotherm
Bershka
Bloomberg
BMW
Boeing
Booz Allen Hamilton
Burberry
Bath & Body Works
Bosch
Bristol Myers Squibb
Capri Holdings
Costa
Carita Paris
CareTrust REIT
Caterpillar
Coach
Cappy
Caudalie
CeraVe
Check Point Software Technologies
Cerelac
Chanel
Chapman and Cutler
Channel
Cheerios
Cheetos
Chevron
Chips Ahoy!
Christina Aguilera
Citi Bank
Carrefour
Codral
Cosco
Canada Dry
Citi
Clal Insurance Enterprises
Clean & Clear
Clearblue
Clinique
Champion
Club Social
Coca Cola
Coffee Mate
Colgate
Comcast
Compass
Caesars
Conde Nast
Cooley LLP
Costco
Côte d’Or
Crest
CV Starr
CyberArk Software
Cytokinetics
Crayola
Cra Z Art
Daimler
Dr Pepper
Del Valle
Daim
Doctor Pepper
Dasani
Doritos
Daz
Dior
Dell
Deloitte
Delta Air Lines
Deutsche Bank
Deutsche Telekom
DHL Group
David Off
Disney
DLA Piper
Domestos
Domino’s
Douglas Elliman
Downy
Duane Morris LLP
Dreft Baby Detergent & Laundry Products
Dreyer’s Grand Ice Cream
eBay
Edelman
Eli Lilly
Evian
Empyrean
Ericsson
Endeavor
EPAM Systems
Estee Lauder
Elbit Systems
Expedia
EY
Forbes
Facebook
Fairlife
Fanta
First International Bank of Israel
Fiverr
Funyuns
Fuze
Fox News
Fritos
Fox Corp
Gatorade
Gamida Cell
GE
Glamglow
General Catalyst
General Motors
Georgia
Gold Peak
Genesys
Goldman Sachs
Grandma’s Cookies
Google
Garnier
Guess
Greenberg Traurig
Guerlain
Givenchy
H&M
Hadiklaim
Huggies
Hanes
HSBC
Head & Shoulders
Hersheys
Herbert Smith Freehills
Hewlett Packard
Hasbro
Hyundai
Henkel
Harel Insurance Investment & Financial Services
Hewlett Packard Enterprise
HubSpot
Huntsman Corp
IBM
Innocent
Insight Partners
Inditex Group
IT Cosmetics
Instacart
Intel
Intermedia
Interpublic Group
Instagram
ICL Group
Intuit
Jazwares
Jefferies
John Lewis
JP Morgan Chase
Jaguar
Johnson & Johnson
JPMorgan
Kenon Holdings
Kate Spade
Kirks’
Kinley Water
KKR
KFC
KKW Cosmetics
Kurkure
Keebler
Kolynos
Kaufland
Kevita
Knorr
KPMG
Lemonade
Lidl
Loblaws
Levi Strauss
Louis Vuitton
Life Water
Levi’s
Levi’s Strauss
LinkedIn
Land Rover
L’Oréal
Lego
Levissima
Live Nation Entertainment
Lufthansa
La Roche-Posay
Lipton
Major League Baseball
Manpower Group
Marriott
Marsh McLennan
Maison Francis Kurkdjian
Mastercard
Mattel
Minute Maid
Monster
Monki
Mainz FC
Mellow Yellow
Mountain Dew
Migdal Insurance
Marks & Spencer
Mirinda
McDermott Will & Emery
Motorola
McKinsey
Merck
Michael Kors
Mizrahi Tefahot Bank
Merck KGaA
Micheal Kors
Milkybar
Maybelline
Mount Franklin
Meta
MeUndies
Mattle
Microsoft
Munchies
Miranda
Morgan Lewis
Moroccanoil
Morgan Stanley
MRC
Nasdaq
Naughty Dog
Nivea
Next
NOS
Nabisco
Nutter Butter
No Frills
National Basketball Association
National Geographic
Nintendo
New Balance
Nutella
Newtons
NVIDIA
Netflix
Nescafe
Nestle
Nesquick
Nike
Nussbeisser
Oreo
Oral B
Old spice
Oysho
Omeprazole
Oceanspray
Opodo
P&G (Procter and Gamble)
Pampers
Pull & Bear
Pepsi
Pfizer
Popeyes
Parker Pens
Philadelphia Cream Cheese
Pizza Hut
Powerade
Purina
Phoenix Holdings
Propel
Ponds
Pure Leaf Green Tea
Power Action Wipes
PwC
Prada
Perry Ellis
Prada Eyewear
Pringles
Payoneer
Procter & Gamble
Purelife
Pureology
Quaker Oats
Reddit
Royal Bank of Canada
Ruffles
Revlon
Ralph Lauren
Ritz
Rolls Royce
Royal
S.Pellegrino
Sabra Hummus
Sabre
Sony
SAP
Simply
Smart Water
Sprite
Schwabe
Shell
Soda Stream
Siemens
StreamElements
Schweppes
Sunsilk
Signal
Skittles
Smart Food
Sobe
Smarties
Sephora
Sam’s Club
Superbus
Samsung
Sodastream
Sunkist
Scotiabank
Sour Patch Kids
Starbucks
Sadaf
Stride
Subway
Tang
Tate’s Bake Shop
The Body Shop
TEVA
Tesco
Twitch
The Ordinary
Tim Hortons
Tostitos
Timberland
Topo Chico
Tapestry
Tropicana
Tommy Hilfiger
Tommy Hilfiger Toiletries
Turbos
Tom Ford
Taco Bell
Triscuit
TUC
Twix
Tottenham Hotspurs
Twisties
Tripadvisor
Uber
Uber Eats
Urban Decay
Upfield
Unilever
Vicks
Victoria’s Secret
V8
Vaseline
Vitaminwater
Volkswagen
Volvo
Walmart
Wegmans
WhatsApp
Waitrose
Woolworths
Wheat Thins
Walkers
Warner Brothers
Warner Chilcot
Warner Music
Wells Fargo
Winston & Strawn
WingStreet
Wissotzky Tea
WWE
Wheel Washing Powder
Wrigley Company
YouTube
Yvel
Yum Brands
Ziyad
Zara
Zim Shipping
Ziff Davis
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afniel · 3 months
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So far no part of the sequel has been written on anything but my phone...why am I like this.
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Like imagine literally only writing on one of these things. Now imagine you've already written a full-ass novel on it. I'm actually very mildly worried that if I get a new phone (this one has battery problems due to age and I've had to glue the entire front panel back on...and the screen protector died so I took it off entirely) that I might somehow Lose My Motivation as if it's got anything at all to do with it.
And like, who cares, even if that ends up true for no reason and I can't write on any other devices (which is demonstrably untrue as I used to write on a fucking IBM 386!! And then a 486, and then a Pentium, because I got my family's hand-me-down computers and I'm old like this) it's still like...I can just use my old phone on wifi. It's whatever. I could write on it until the screen dies and it's fine. It'll probably still be an alarm clock anyway. I had a used iPhone that I traded art for once that I literally only ever used on wifi because I never got it a SIM card and it was kind of neat actually. Not my first rodeo.
But also I've got to convince myself that I don't need another Z Flip because the screen protector does really blow, even if everything else about it is cool and I love the form factor a lot. I mean look at it. It's basically a Game Boy Advance SP. I loved those guys. They were so good.
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(Let's be real though, if they're making purple Z Flip5s I'm gonna end up with another one, and they are, so...)
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harrelltut · 7 months
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u scared [u.s.] of us schwarz heil trillionaires... worth $144,000 quadrillion?!?!?!
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we extra [we] dark HEIL [HELL = HARRELL] wealth dynasty!!!
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SCHWARZ DEUTSCH MILITÄR KNOT SEE [Z] TECHNOCRACY = QUANTUM HARRELL TECH LLC
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shhh... the deaf dumb & dumber dumber clones [d.c.] of mass american idiocracy [a.i.]... will never understand us... don't tell them nothing
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uh oh... your artificial cgi space.gov got some american idiocracy [a.i.] explaining to do
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quantumharrelltech.ca.gov Outside harrelltut.com’s Astronomical MARS’ GOLDEN Firmament Water Dome OVER Earth [Qi]
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black deutsch wall street 6g - 18g telecom patents @ quantum harrell tech llc
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HEIL 1968-michaelharrelljr.com Domain Creator [D.C.] @ quantumharrelltech.ca.gov!!!... like Adolf did 
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ANU SCHWARZ IRON IGIGI SKY REICH @ quantumharrelltech.com?!?!?!... YES!!!
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HEIL 1968-michaelharrelljr.com Domain Creator [D.C.] @ quantumharrelltech.ca.gov!!!... like Osama bin Laden did 
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HEIL 1968-michaelharrelljr.com Domain Creator [D.C.] @ quantumharrelltech.ca.gov!!!... like Muammar Gaddafi did 
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HEIL 1968-michaelharrelljr.com Domain Creator [D.C.] @ quantumharrelltech.ca.gov!!!... like Idi Amin did 
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eye schwarz deutsch 1968-michaelharrelljr.com militär knot see [z]… conquering kangsolomon.com @ quantumharrelltech.ca.gov 
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eye love [el] my ancient earth [qi] swastika powers
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© 1698-2223 QUANTUM HARRELL TECH LLC All LOST ANCIENT [L.A.] ATLANTEAN DNA [A.D.] DotCom [A.D.] + DotTech [A.D.] + Pre 1698quantumharrellgov.tech Domain Name Rights Reserved @ quantumharrelltech.ca.gov
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szonikuscsavarhuzo · 7 months
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Akkor ennyit a jól fizetett cobol programozókról
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slavicprincess02 · 8 months
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Dziś rano wstałam i zobaczyłam powiadomienie od Tomka z Czech z wiadomością o tym, ze mnie kocha XDD
Ehh.. men are lonely… a to tylko jakieś 3 tygodnie odpisywanie na „Dobranoc” i „Miłego dnia”. Nawet nie przeczytałam tych kocopołów do końca. Trochę smutne, trochę śmieszne.
Dziś rano nie wzięłam udziału w stand up meeting bo się wstydziłam, jakoś głupio mi było dołączyć do spotkania bo bałam się pytań odnośnie tego co robie, kiedy będę itd. To głupie, irracjonalne, ale jak już chyba mówiłam… wciąż jestem pizda. Wciąż bezpodstawnie boje się jakichś rzeczy. Bez sensu. Jestem jakaś strachliwa…
Jutro lecę do Szwecji. Nie chce mi się. Nie wyczekuje tego, nie spieszy mi się. Chyba najfajniejsze w tym wszystkim jest to, ze jadę przez Gdansk. I ze będę mogła kupić sobie mrożony falafel. A tak to? Hmm… przez cały tem czas wakacji nie zatęskniłam ani trochę. Wręcz przeciwnie. Chciało mi się płakać na myśl o powrocie. Do tej ponurej, nudnej, depresyjnej Szwecji. Ale dziś Maarten trochę mnie rozweslił pytając, czy chce iść z nim na saunę w środę. Mówił tez, ze wpadli do niego znajomi z Belgii i ze poznamy się w środę na saunie właśnie. Chociaż to teraz. No i w weekend może pójdziemy na caoing albo kajaki. W sumie nigdy nie byłam i nie będę mieć co robić, więc spoko.
Poza tym mam teraz nowe zajęcie w Volvo w przypadku nudy. Zamierzam w końcu zacząć robić kurs Data Science z IBM. Sporo czasu i nuda, więc chociaż to jakoś spożytkuję. Oczywiście jest to efekt mojej ostatniej małej porażki (?) związanej z ofertą stażu w BMW. A może to wcale nie porażka, tylko sytuacja, która miała mi dać do zrozumienia, że powinnam się za siebie wziąć? Kurde, znajomi Maróna, jak sam mówił, maja ich po 5, 8… ja żadnego. Widać ewidentnie, że są mega ambitni i pracowici. Ale maja tez motywacje - wyjazd z Libanu. Ja na 1 i 2 latach studiów też byłam mega zmotywowana, więc też cisnęłam - żeby zdać, żeby dostać stypendium, żeby pokazać (komu?), że jestem równie dobra lub lepsza od Seby.
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hydralisk98 · 8 months
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Short sum for newbie system designer processor steps
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Here are a few beginner projects for learning the ropes of customized computation architecture design:
Pana, a '4-4-4' instruction processor derived from Intersil 6100 & GaryExplains' but for 4-bit data. Uses the sixteen (16) RISC instructions shown by GaryExplains and only four (4) of its registers (ACC, PC, LN & MQ) as per of the Intersil 6100 specification. Doing as much work onto nibbles like an MVP Intel 4004 can, great as a BCD & Nibble data converter for later designs.
Tina, a barely expanded '4-4-8' processor derived from the "Pana" design, it uses more registers by adding twelve general-use registers (A-F, U-Z letters) and operate onto a single byte of data at a time. Great for two nibbles operations, byte-wise interoperability and 8-bit word compatibility with all sorts of modern processors from the seventies-onwards.
Milan, a '6-2-24' strong hybrid 8-bit / 12-bit processor derived from the "Tina" design, operating onto three bytes or two tribbles of data at once depending of use-case, while fitting in exactly 32-bit per instruction. Aimed at computing three 8-bit units, enabling 16-bit & 24-bit compatibility as well as up to two tribble operands. A great MVP implementation step towards my next own tribble computing architecture and a competitor to the Jack educational computer as shown in the NAND2Tetris courseware book.
When I am done with such, I will be onto three tribble-oriented architectures for lower-end, middle-end and upper-end "markets". Zara being lower-end (6-bit opcode, 6-bit register & 36-bit data = 48-bit instructions), Zorua being mid-end (8-bit opcode, 8-bit register and 48-bit data = 64-bit instructions) and Zoroark being upper-end (12-bit opcode, 36-bit register and 96/144-bit data (so either eight or twelve tribble operands worth of data) = 144/192-bit instructions, aiming to emulate close enough to an open-source IBM's PowerISA clone with VLIW & hot-swap computer architecture).
By the way, I haven't forgotten about the 16^12 Utalics game consoles and overall tech market overview + history specifications, nor have I forgotten about studying + importing + tinkering around things like Microdot & Gentoo & Tilck. I simply need to keep a reminder to myself for what to do first when I shall start with the computation engineering process. Hopefully that might be interesting for you to consider as well... Farewell!
EDIT #1
youtube
Tweaked and added some additional text & considering studying various aspects of Linux and overall copyleft / open source culture engineering scene, especially over Gentoo alternative kernels & hobby / homebrew standalone operating systems (GNU Hurd, OpenIndiana, Haiku... as well as niche ones like ZealOS, Parade, SerenityOS...) as to design a couple computation ecosystems (most derived from my constructed world which takes many hints from our real-life history) and choosing one among them to focus my implementation efforts onto as the "Nucleus" hybrid modular exo-kernel + my very own package modules collection. (Still aiming to be somewhat compatible with existing software following Unix philosophy principles too as to ease the developer learning cost in initial infrastructure compatibility & overall modularized complexity; Might also use some manifestation tips & games to enrich it with imports from said constructed world if possible)
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Patrząc na same liczby, niesamowite 😲 Ale z drugiej strony - to giganci na rynku 💪 Zaskakują Was ilości serwerów w tych firmach? 🤔
▶ IBM - dokładna ilość serwerów nie jest znana. Ale wiadomo na jakiej powierzchni - 8 milionów stóp kwadratowych tj. ponad 740.000 m2 😲
▶ eBay - ponad 50.000 serwerów
▶ Rackspace - ponad 95.000 serwerów
▶ Akamai Technologies - ponad 127.000 serwerów
▶ OVH - 150.000 serwerów
▶ Google - nieoficjalnie ponad 900.000 serwerów - wartość ponad 200mln euro
▶ Amazon - ponad 500.000 serwerów
▶ Facebook - “setki tysięcy” :)
▶ Microsoft - ponad 1.000.000 serwerów
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stevenodickens · 2 years
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Banking
44 of the top 50 banks and other financial institutes run on IBM Z mainframes.
Banks of all kinds are required to process massive amounts of data. High-frequency trading is a priority for investment banks, and they must react quickly to changes in the financial markets. All banks must execute huge volumes of transactions in financial services, which includes credit card payments, Cash withdrawal, and online account updates. Mainframes are used by banks to handle data at a speed that traditional servers cannot meet.
 Personal banks, as reliant on mainframe computing as they are, pale in comparison to investment banks that routinely engage in high-frequency trading. These businesses require a lot of processing power since they not only have consumers but also need to react rapidly to any shifts or changes in the financial market. That drive is aided by the processing capacity of mainframe computers, which keeps the company ahead of the competition. That is why, no matter how big or little, every bank needs mainframe computers to maintain track of data and sort through thousands of transactions. The computational power of commodity servers is simply insufficient to manage such massive amounts of data.
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mikesfulton · 2 years
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IBM Z and Cloud Modernization Stack Uncovered
See how IBM Z and Cloud Modernization Stack streamlines software installation and configuration
IBM Z and Cloud Modernization Stack In my last article, I introduced the IBM Z and Cloud Modernization Stack. In this article, I’ll dig into installation, configuration, and usage of the installed software. Installing Software on z/OS with z/OS Cloud Broker To install software with z/OS Cloud Broker on a z/OS endpoint, you first need to install the z/OS Package Manager, which runs natively on…
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a1wsx · 2 years
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gulp dat glizzy girl!!
NEC PC-9801 – nie w pełni kompatybilna z przemysłowym standardem PC lina komputerów osobistych stworzona w 1982 w Japonii przez NEC Corporation na bazie rozwiązań IBM, skierowana wyłącznie na rynek japoński. NEC zaprzestał jej produkcji w 2000 roku.
Pierwszy model był architekturą 16-bitową z procesorem Intel 8086 taktowanym zegarem 5 MHz oraz 128 KB pamięci RAM. Dostarczany z kartami grafiki zdolnymi wyświetlać 8 kolorów w rozdzielczości 640x400 - co wyraźnie wyróżniało się osiągami w stosunku do ówczesnych PC.
Początkowo pomyślany jako rozwiązanie dla zastosowań przemysłowych i biurowych, w roku 1987 seria PC-9801 zajęła blisko 90% japońskiego rynku komputerów osobistych[1]. Z czasem, wraz ze wzrostem mocy i docenieniem efektów graficznych i dźwiękowych przez użytkowników domowych (zwłaszcza graczy) stał się popularny także w niekomercyjnych zastosowaniach – debiutowała na nich np. seria Touhou Project[2].
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