Some predictions for the IT industry

Artificial intelligence (AI) and machine learning (ML) will continue to advance and be increasingly adopted across various sectors. AI and ML technologies enable computers to perform tasks that would normally require human intelligence, such as recognizing patterns, making decisions, and learning from data. These technologies have the potential to revolutionize many industries, including healthcare, finance, and manufacturing.

The Internet of Things (IoT) will see widespread adoption and become a key driver of digital transformation in businesses. The IoT refers to the interconnected network of physical devices, such as sensors and appliances, that are able to collect and exchange data. This technology has the potential to enable businesses to increase efficiency, reduce costs, and improve customer experiences.

Cloud computing will continue to grow in popularity and become the dominant model for delivering IT services. Cloud computing refers to the delivery of computing resources, such as storage, processing power, and software, over the internet. This model enables businesses to access IT resources on-demand and pay only for what they use, rather than having to invest in and maintain their own infrastructure.

Cybersecurity will remain a top concern for businesses, as the threat of cyberattacks continues to evolve and increase. Cybersecurity refers to the practices and technologies designed to protect networks, devices, and data from unauthorized access or attacks. As more businesses move to the cloud and adopt new technologies, the need for effective cybersecurity measures will continue to grow.

The adoption of 5G networks will accelerate, leading to increased connectivity and the proliferation of new technologies such as virtual and augmented reality. 5G is the fifth generation of cellular network technology, and it offers faster speeds and lower latency than previous generations. The widespread adoption of 5G networks will enable the development of new technologies that require high-speed connectivity, such as virtual and augmented reality.

Blockchain technology will see increasing adoption, particularly in the financial industry, but also in other sectors such as supply chain management and healthcare. Blockchain is a distributed database that allows multiple parties to record and verify transactions without the need for a central authority. This technology has the potential to increase transparency and security in a variety of industries.

The use of big data analytics will continue to grow, enabling businesses to make data-driven decisions and gain competitive advantages. Big data refers to the large volumes of structured and unstructured data that are generated by businesses and organizations. By analyzing this data, businesses can identify patterns, trends, and insights that can inform decision-making and strategy.

The demand for skilled IT professionals, particularly in areas such as data science and cybersecurity, will continue to outpace supply. The growing adoption of new technologies and the increasing reliance on IT systems means that there is a high demand for professionals with the skills and knowledge to design, build, and maintain these systems.

The use of automation and robotics will increase, leading to the creation of new job roles and the transformation of existing ones. Automation refers to the use of technology to perform tasks that were previously done by humans. As automation becomes more prevalent, it will change the way that work is done and create new job opportunities in areas such as programming and data analysis.

The use of virtual and remote work will continue to grow, enabled by advances in collaboration and communication technologies. The COVID-19 pandemic has accelerated the trend toward remote work, and it is likely that this trend will continue even after the pandemic ends. Collaboration and communication technologies, such as videoconferencing and project management software, will enable teams to work effectively from anywhere.

Locus Robotics secures $117M Series F

- By Nuadox Crew -

US-based Locus Robotics, a forerunner in autonomous mobile robots (AMR) for fulfillment and distribution facilities, announced a $117 million Series F funding round on November 29 led by Goldman Sachs Asset Management and G2 Venture Partners.

With over 230 contract sites around the world, some with as many as 500 LocusBots per site, the Locus solution aims to efficiently and seamlessly orchestrate the operation and management of multiple robot form factors, as well as providing forward-looking, real-time business intelligence.

--

Source: Locus Robotics

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Calculating the ‘fingerprints’ of molecules with artificial intelligence — ScienceDaily

With conventional methods, it is extremely time-consuming to calculate the spectral fingerprint of larger molecules. But this is a prerequisite for correctly interpreting experimentally obtained data. Now, a team at HZB has achieved very good results in significantly less time using self-learning graphical neural networks. “Macromolecules but also quantum dots, which often consist of thousands…

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So I don't know how people on this app feel about the shit-house that is TikTok but in the US right now the ban they're trying to implement on it is a complete red herring and it needs to be stopped.

They are quite literally trying to implement Patriot Act 2.0 with the RESTRICT Act and using TikTok and China to scare the American public into buying into it wholesale when this shit will change the face of the internet. Here are some excerpts from what the bill would cover on the Infrastructure side:

SEC. 5. Considerations.

(a) Priority information and communications technology areas.—In carrying out sections 3 and 4, the Secretary shall prioritize evaluation of— (1) information and communications technology products or services used by a party to a covered transaction in a sector designated as critical infrastructure in Policy Directive 21 (February 12, 2013; relating to critical infrastructure security and resilience);

(2) software, hardware, or any other product or service integral to telecommunications products and services, including— (A) wireless local area networks;

(B) mobile networks;

(C) satellite payloads;

(D) satellite operations and control;

(E) cable access points;

(F) wireline access points;

(G) core networking systems;

(H) long-, short-, and back-haul networks; or

(I) edge computer platforms;

(3) any software, hardware, or any other product or service integral to data hosting or computing service that uses, processes, or retains, or is expected to use, process, or retain, sensitive personal data with respect to greater than 1,000,000 persons in the United States at any point during the year period preceding the date on which the covered transaction is referred to the Secretary for review or the Secretary initiates review of the covered transaction, including— (A) internet hosting services;

(B) cloud-based or distributed computing and data storage;

(C) machine learning, predictive analytics, and data science products and services, including those involving the provision of services to assist a party utilize, manage, or maintain open-source software;

(D) managed services; and

(E) content delivery services;

(4) internet- or network-enabled sensors, webcams, end-point surveillance or monitoring devices, modems and home networking devices if greater than 1,000,000 units have been sold to persons in the United States at any point during the year period preceding the date on which the covered transaction is referred to the Secretary for review or the Secretary initiates review of the covered transaction;

(5) unmanned vehicles, including drones and other aerials systems, autonomous or semi-autonomous vehicles, or any other product or service integral to the provision, maintenance, or management of such products or services;

(6) software designed or used primarily for connecting with and communicating via the internet that is in use by greater than 1,000,000 persons in the United States at any point during the year period preceding the date on which the covered transaction is referred to the Secretary for review or the Secretary initiates review of the covered transaction, including— (A) desktop applications;

(B) mobile applications;

(C) gaming applications;

(D) payment applications; or

(E) web-based applications; or

(7) information and communications technology products and services integral to— (A) artificial intelligence and machine learning;

(B) quantum key distribution;

(C) quantum communications;

(D) quantum computing;

(E) post-quantum cryptography;

(F) autonomous systems;

(G) advanced robotics;

(H) biotechnology;

(I) synthetic biology;

(J) computational biology; and

(K) e-commerce technology and services, including any electronic techniques for accomplishing business transactions, online retail, internet-enabled logistics, internet-enabled payment technology, and online marketplaces.

(b) Considerations relating to undue and unacceptable risks.—In determining whether a covered transaction poses an undue or unacceptable risk under section 3(a) or 4(a), the Secretary— (1) shall, as the Secretary determines appropriate and in consultation with appropriate agency heads, consider, where available— (A) any removal or exclusion order issued by the Secretary of Homeland Security, the Secretary of Defense, or the Director of National Intelligence pursuant to recommendations of the Federal Acquisition Security Council pursuant to section 1323 of title 41, United States Code;

(B) any order or license revocation issued by the Federal Communications Commission with respect to a transacting party, or any consent decree imposed by the Federal Trade Commission with respect to a transacting party;

(C) any relevant provision of the Defense Federal Acquisition Regulation and the Federal Acquisition Regulation, and the respective supplements to those regulations;

(D) any actual or potential threats to the execution of a national critical function identified by the Director of the Cybersecurity and Infrastructure Security Agency;

(E) the nature, degree, and likelihood of consequence to the public and private sectors of the United States that would occur if vulnerabilities of the information and communications technologies services supply chain were to be exploited; and

(F) any other source of information that the Secretary determines appropriate; and

(2) may consider, where available, any relevant threat assessment or report prepared by the Director of National Intelligence completed or conducted at the request of the Secretary.

Look at that, does that look like it just covers the one app? NO! This would cover EVERYTHING that so much as LOOKS at the internet from the point this bill goes live.

It gets worse though, you wanna see what the penalties are?

(b) Civil penalties.—The Secretary may impose the following civil penalties on a person for each violation by that person of this Act or any regulation, order, direction, mitigation measure, prohibition, or other authorization issued under this Act: (1) A fine of not more than $250,000 or an amount that is twice the value of the transaction that is the basis of the violation with respect to which the penalty is imposed, whichever is greater. (2) Revocation of any mitigation measure or authorization issued under this Act to the person. (c) Criminal penalties.— (1) IN GENERAL.—A person who willfully commits, willfully attempts to commit, or willfully conspires to commit, or aids or abets in the commission of an unlawful act described in subsection (a) shall, upon conviction, be fined not more than $1,000,000, or if a natural person, may be imprisoned for not more than 20 years, or both. (2) CIVIL FORFEITURE.— (A) FORFEITURE.— (i) IN GENERAL.—Any property, real or personal, tangible or intangible, used or intended to be used, in any manner, to commit or facilitate a violation or attempted violation described in paragraph (1) shall be subject to forfeiture to the United States. (ii) PROCEEDS.—Any property, real or personal, tangible or intangible, constituting or traceable to the gross proceeds taken, obtained, or retained, in connection with or as a result of a violation or attempted violation described in paragraph (1) shall be subject to forfeiture to the United States. (B) PROCEDURE.—Seizures and forfeitures under this subsection shall be governed by the provisions of chapter 46 of title 18, United States Code, relating to civil forfeitures, except that such duties as are imposed on the Secretary of Treasury under the customs laws described in section 981(d) of title 18, United States Code, shall be performed by such officers, agents, and other persons as may be designated for that purpose by the Secretary of Homeland Security or the Attorney General. (3) CRIMINAL FORFEITURE.— (A) FORFEITURE.—Any person who is convicted under paragraph (1) shall, in addition to any other penalty, forfeit to the United States— (i) any property, real or personal, tangible or intangible, used or intended to be used, in any manner, to commit or facilitate the violation or attempted violation of paragraph (1); and (ii) any property, real or personal, tangible or intangible, constituting or traceable to the gross proceeds taken, obtained, or retained, in connection with or as a result of the violation. (B) PROCEDURE.—The criminal forfeiture of property under this paragraph, including any seizure and disposition of the property, and any related judicial proceeding, shall be governed by the provisions of section 413 of the Controlled Substances Act (21 U.S.C. 853), except subsections (a) and (d) of that section.

You read that right, you could be fined up to A MILLION FUCKING DOLLARS for knowingly violating the restrict act, so all those people telling you to "just use a VPN" to keep using TikTok? Guess what? That falls under the criminal guidelines of this bill and they're giving you some horrible fucking advice.

Also, VPN's as a whole, if this bill passes, will take a goddamn nose dive in this country because they are another thing that will be covered in this bill.

They chose the perfect name for it, RESTRICT, because that's what it's going to do to our freedoms in this so called "land of the free".

Please, if you are a United States citizen of voting age reach out to your legislature and tell them you do not want this to pass and you will vote against them in the next primary if it does. This is a make or break moment for you if you're younger. Do not allow your generation to suffer a second Patriot Act like those of us that unfortunately allowed for the first one to happen.

And if you support this, I can only assume you're delusional or a paid shill, either way I hope you rot in whatever hell you believe in.

The food bank is located in an unremarkable industrial area in east-end Ottawa. It does not even directly serve the public, but operates as a distribution warehouse for supplying partner agencies who do. CEO Rachael Wilson said the article attracted shock, eye-rolls and some laughter among staff there. "We were quite surprised to see that we had made this list," she said. "Thankfully everyone so far has realized that this clearly was not an article that we were a part of and it's pretty obvious that a robot wrote this." The article carried the byline "Microsoft Travel." There is nothing on the page that identifies it as the product of artificial intelligence, but the company later acknowledged that it was generated by algorithms subject to human review. It suggested that it was the human review, not the algorithm, that fell short.

It seems to be a recurring pattern that corporations who use AI offload the blame onto "human review" but if the humans in your process can't or aren't willing to review algorithmically-generated content, then you should probably stop making it altogether.

THE CREATOR (2023)

Starring John David Washington, Madeleine Yuna Voyles, Gemma Chan, Ken Watanabe, Sturgill Simpson, Allison Janney, Ralph Ineson, Marc Menchaca, Veronica Ngo, Amar Chadha-Patel, Robbie Tann, Michael Esper, Veronica Ngo, Ian Verdun, Daniel Ray Rodriguez, Rad Pereira, Syd Skidmore, Karen Aldridge, Teerawat Mulvilai and Leanna Chea.

Screenplay by Gareth Edwards and Chris Weitz.

Directed by Gareth Edwards.

Distributed by 20th Century Studios. 133 minutes. Rated PG-13.

Artificial Intelligence has been hugely in the news in recent months. Is it simply a tool, or is it potentially dangerous?

Therefore, it’s probably a wise time for this smart and thoughtful sci-fi film to take a hard look at AI – and to look at it from a potentially different viewpoint. This is because in The Creator, AI robots are generally looked at with compassion. In fact, it is the human beings who come off looking bad.

Hmm… Interesting take on it.

Not that it is the most astoundingly original take. Stephen Spielberg’s AI: Artificial Intelligence trod on somewhat similar ground. It also takes more than a few pages from the Avatar playbook, and also a few from Black Panther and several other sci-fi epics. Still, it is a timely subject now, and The Creator is probably a bit better than its occasionally cliched parts.

However, it does create a spectacularly evocative future world which overwhelms some of the movie’s less original storyline impulses. Written by Gareth Edwards (Rogue One) and Chris Weitz (who has come a long way from American Pie), it tells the story of a rogue group of AI robots hiding out to create their own Utopian colony while the army (as represented by a surprisingly hard-ass soldier played against type by Allison Janney) searches the world trying to destroy them. They are in particular looking for the perhaps mythical inventor of the AI, known only as “The Creator.”

The center of the story is Joshua (John David Washington), a disabled soldier who has been working undercover with the army to track down the robots. However, after he befriends a robot community and falls for one of their lot (Gemma Chan), he seems to have a change of heart. When he is given the responsibility of caring for a young AI girl (Madeleine Yuna Voyles) who is integral to robot survival, he travels the world trying to keep her safe as his old friends and co-workers track them down.

But is he really betraying his mission, or is he simply double crossing the robots?

Like I said, it’s hardly the most original film idea ever. (A cynic might suggest it could have been written by AI, but that is hardly fair.)

However, the spectacular visuals that make up this dystopian world definitely make The Creator worth seeing. Edwards has a keen visual eye and creates one of the more impressive future worlds in recent memory, and immersing yourself in that world is the type of experience that the movies are created for. Doubly so if you get to see the film in IMAX.

Jay S. Jacobs

Copyright ©2023 PopEntertainment.com. All rights reserved. Posted: September 29, 2023.

I think if people like this character and I see an asset, I'll make a comic about them . His name is Bon-Bon, he works in a cafe where he loves to cook all kinds of baked goods (he also loves baked goods a lot). He is introverted, so he usually communicates through a robot, which he considers his son and is called Rob, Rob is endowed with artificial intelligence and distributes food to the customers

Honestly the thing I find kind of frightening about the recent wave of large language models is the degree to which they developed capabilities that we did not explicitly give them. Like more and more it seems like transformers are a truly universal architecture that can do almost any task you can give them.

Like okay, they can do a little bit of math and solve some simple logic puzzles. The thing that I find so so startling is that they get this and also the common sense reasoning necessary to solve them without there being specialized architectures for those things. There's been a ton of work on trying to plug machine learning algorithms into formal reasoning models and trying to learn them together. Neural Turing machines, differentiable neural computers, Markov logic networks, fuzzy logic, neurosymbolic languages like Scallop and Neuralogic. This is decades of work from half a dozen different angles. Turns out you don't need it. Just make the model bigger and it can do math.

What about vision? It's a field with a long history. hand engineered features like wavelets gave way to convolutional networks, but those are also being replaced by guess what? that's right transformers! You dont even really need to think about the structure of the problem, just feed it to a transformer and also feed it text, and the fact that it's jointly trained with language improves its performance.

What about planning in robotics? Again, field with 50+ years of research. Turns out GPT actually just solves this too with no robot- or planning-focused training at all. All you have to do is ask it to write a plan and it'll give you one, a lot more easily than we could with the existing frameworks we've spent 50 years developing.

This is why it's driving me nuts seeing all these posts dumping on alignment concerns by saying "oh but intelligence isn't just one thing, just because GPT is good at text generation doesn't mean it'll be good at all the other things we call intelligence". This is completely missing the point. Whether or not it's necessarily true, what we're rapidly finding is that the current generation of language models very much are able to solve a wide variety of tasks, even for things it wasn't specially trained for. I cannot emphasize enough that what's concerning about this is 1) nobody was trying to make a model that could specifically do math or reasoning or planning. There's no specialized math or planning part of the model. It just figured out how to do them. 2) The transformer architecture seems to be a fully general, or nearly fully general, tool for learning from almost any kind of data. The paper that introduced the model was called Attention is All You Need, and that's only proven to be more and more true over time. For many tasks, attention really is all you need. It really feels like we're getting a lot closer to truly general artificial intelligence.

Now, I do actually think there are some things separating our current knowledge from building something really generally intelligent, and several more that separate us from making super-human level intelligence (most notably, while you can probably get human level intelligence from imitating humans, I don't think you can get superhuman intelligence this way -- you need some way of reasoning about exploration and how to gather new out-of-distribution data). But by far the longest standing open problem in AI has not been "how to do reasoning" or "how to do math", but "how to encode common-sense reasoning into an AI". It's an old enough problem that philosophers have built careers talking about why it's so hard. And I cannot stress enough that this problem, long considered to be the holy grail of the field, is now very close to being solved, if it isn't solved already. GPT-3 gets 65% on Winograd schemas, and GPT-4 gets nearly 95%. Is anybody really betting against the idea that GPT-5 will get 99.8% or higher? It would not at all surprise me if a lot of the other problems after this, like enabling long chains of correct reasoning, ended up being easier than this one.

AI: A Misnomer

As you know, Game AI is a misnomer, a misleading name. Games usually don't need to be intelligent, they just need to be fun. There is NPC behaviour (be they friendly, neutral, or antagonistic), computer opponent strategy for multi-player games ranging from chess to Tekken or StarCraft, and unit pathfinding. Some games use novel and interesting algorithms for computer opponents (Frozen Synapse uses deome sort of evolutionary algorithm) or for unit pathfinding (Planetary Annihilation uses flow fields for mass unit pathfinding), but most of the time it's variants or mixtures of simple hard-coded behaviours, minimax with alpha-beta pruning, state machines, HTN, GOAP, and A*.

Increasingly, AI outside of games has become a misleading term, too. It used to be that people called more things AI, then machine learning was called machine learning, robotics was called robotics, expert systems were called expert systems, then later ontologies and knowledge engineering were called the semantic web, and so on, with the remaining approaches and the original old-fashioned AI still being called AI.

AI used to be cool, then it was uncool, and the useful bits of AI were used for recommendation systems, spam filters, speech recognition, search engines, and translation. Calling it "AI" was hand-waving, a way to obscure what your system does and how it works.

With the advent if ChatGPT, we have arrived in the worst of both worlds. Calling things "AI" is cool again, but now some people use "AI" to refer specifically to large language models or text-to-image generators based on language models. Some people still use "AI" to mean autonomous robots. Some people use "AI" to mean simple artificial neuronal networks, bayesian filtering, and recommendation systems. Infuriatingly, the word "algorithm" has increasingly entered the vernacular to refer to bayesian filters and recommendation systems, for situations where a computer science textbook would still use "heuristic". Computer science textbooks still use "AI" to mean things like chess playing, maze solving, and fuzzy logic.

Let's look at a recent example! Scott Alexander wrote a blog post (https://www.astralcodexten.com/p/god-help-us-lets-try-to-understand) about current research (https://transformer-circuits.pub/2023/monosemantic-features/index.html) on distributed representations and sparsity, and the topology of the representations learned by a neural network. Scott Alexander is a psychiatrist with no formal training in machine learning or even programming. He uses the term "AI" to refer to neural networks throughout the blog post. He doesn't say "distributed representations", or "sparse representations". The original publication he did use technical terms like "sparse representation". These should be familiar to people who followed the debates about local representations versus distributed representations back in the 80s (or people like me who read those papers in university). But in that blog post, it's not called a neural network, it's called an "AI". Now this could have two reasons: Either Scott Alexander doesn't know any better, or more charitably he does but doesn't know how to use the more precise terminology correctly, or he intentionally wants to dumb down the research for people who intuitively understand what a latent feature space is, but have never heard about "machine learning" or "artificial neural networks".

Another example can come in the form of a thought experiment: You write an app that helps people tidy up their rooms, and find things in that room after putting them away, mostly because you needed that app for yourself. You show the app to a non-technical friend, because you want to know how intuitive it is to use. You ask him if he thinks the app is useful, and if he thinks people would pay money for this thing on the app store, but before he answers, he asks a question of his own: Does your app have any AI in it?

What does he mean?

Is "AI" just the new "blockchain"?

HE-RObot (2008) by Heathkit Educational Systems, Benton Harbor, MI. In December 2007, Heathkit announced it would distribute an educational version of White Box Robotics' PC-BOT to be known as the HE-RObot. “Whether you and your students want to write custom algorithms for artificial intelligence or just want an entertaining learning tool, Heathkit's HE-RObot™ can do the job. Built with a compact design for optimal mobility, HE-RObot™ utilizes industry standard PC hardware and software providing the most versatile and user-friendly robot on the market today. Controlled by remote or set to move autonomously, it is capable of sensing its environment, reacting and moving around obstacles. HE-RObot™ can talk, see, hear, transmit receive and process data, or if you like, just play a CD. By being able to do just about anything, HE-RObot™ provides students and teachers with a friendly, personable technological experience.”

Scientists use power of AI to supercharge planetary studies

A new technique for detecting planetary craters which will allow scientists to accurately map the surfaces of planets using different types of data has been described as a "game-changer" which could be used in future space missions.

A team of researchers from the University of Aberdeen has developed a new universal crater detection algorithm (CDA) using META AI’s Segment Anything Model (SAM).

SAM, released earlier this month, is a new artificial intelligence model that can automatically ‘cut out’ any object in any image.

The technology has enabled the team to automatically map craters instead of doing so manually – a time-consuming process. At the same time, the use of different types of data allows for more accurate and flexible surface characterisation.

The CDA approach can work with different data and celestial bodies, giving it the potential to be a universal solution for crater detection in various planetary surfaces.

It could also help identify possible landing sites for robotic or human missions, and potentially be used for automatic navigation based on terrain observations.

Dr Iraklis Giannakis, from the University’s School of Geosciences, led the research in collaboration with colleagues from the University. A preprint of the results has been published in arXiv.

Dr Giannakis said: “Crater detection is a crucial task in planetary science enabling us to better understand the geology, history, and evolution of celestial bodies such as Mars, the Moon, and other planets.

“Our universal CDA approach leverages the power of SAM to automatically detect craters with high accuracy and efficiency, reducing the need for manual identification.

“With its advanced segmentation capabilities, SAM has proven to be a game-changer for CDA, allowing us to accurately identify craters of various sizes, shapes, and orientations – even in challenging terrain conditions.”

Dr Giannakis said the development of the CDA has created new possibilities for planetary science as well as for future exploration missions.

“By automatically mapping craters scientists can study their distribution, size, and morphology to better understand the planetary surface and its evolution over time. This can help in uncovering the geological history, surface processes, and potential habitability of a planet or moon.

“Craters can also be potential sources of valuable resources, such as water ice on planetary bodies like the Moon or Mars. By automatically mapping craters, scientists can identify potential locations where resources may be concentrated, which can be important for future human missions and for planning resource utilisation strategies in space exploration scenarios.”

Robot Dreams (2023, Spain/France)

There exists an assumption that one has to be an animator in order to direct an animated film. While most cinephiles might reflexively point to Wes Anderson (2009’s Fantastic Mr. Fox, 2018’s Isle of Dogs), I think Isao Takahata (1988’s Grave of the Fireflies, 1991’s Only Yesterday) the exemplar here. Even so, a non-animator taking the reins of an animated movie is rare. Into that fold steps Pablo Berger, in this adaptation of Sara Varon’s graphic novel Robot Dreams. Moved after reading Varon’s work in 2010, Berger acquired Varon’s “carte blanche” permission to make a 2D animated adaptation however he saw fit. Like the graphic novel, Berger’s Robot Dreams is also dialogue-free.

Beginning production on Robot Dreams proved difficult. Berger originally teamed with Ireland’s Cartoon Saloon (2009’s The Secret of Kells, 2020’s Wolfwalkers) to make Robot Dreams, but these plans fell wayside when the COVID-19 pandemic hit. His schooling in how to make an animated film would come quickly. Despite an increased appetite for Spanish animation worldwide (2019’s Klaus, 2022’s Unicorn Wars), poor distribution and marketing of domestically-made animated movies has often meant Spanish animators have roved around Europe looking for work. With a pandemic sending those Spanish animators home, Berger and his Spanish and French producers set up “pop-up studios” in Madrid and Pamplona, purchased the infrastructure and space needed to make an animated feature, and recruited and hired animators. Berger’s admiration of animated film fuses the lessons of silent film acting (Berger made a gorgeous silent film in 2012’s Blancanieves; in interviews, Berger cites Charlie Chaplin’s movies as having the largest influence on Robot Dreams, alongside Takahata’s films) to result in one of the most emotionally honest films of the decade thus far – animated or otherwise.

Somewhere in Manhattan in the late 1980s in a world populated entirely of anthropomorphized animals, we find ourselves in Dog’s apartment. Dog, alone in this world, consuming yet another TV dinner, is channel surfing late one evening. He stumbles upon a commercial advertising a robot companion. Intrigued, he orders the robot companion and, with some difficulty, assembles Robot. The two become fast friends as they romp about New York City over a balmy summer, complete with walks around their neighborhood and Central Park, street food, trips to Coney Island, and roller blading along to the groovy tunes of Earth, Wind & Fire. At summer’s end, an accident sees the involuntary separation of Dog and Robot, endangering, for all that the viewer can assume, the most meaningful friendship in Dog’s life and Robot’s brief time of existence.

If you have not seen the film yet, let me address a popular perception early on in this piece. Set in a mostly-analog 1980s, Robot Dreams contains none of the agonizing over artificial intelligence or automatons in fashion in modern cinema. There is no commentary about how technology frays an individual’s connections to others. Robot is a rudimentary creation, closer to a sentient grade school science project than a Data or T-1000.

So what is Robot Dreams saying instead? Principally, it is about the loving bonds of friendship – how a friend can provide comfort and company, how they uplift the best parts of your very being. For Robot, the entirety of their life prior to the aforementioned accident (something that I, for non-viewers, am trying not to spoil as Robot Dreams’ emotional power is fully experienced if you know as little as possible) has been one of complete estival bliss. Robot, in due time, discovers that one of the most meaningful aspects of friendship is that such relationships will eventually conclude – a fundamental part of life. And for Dog, Robot’s entrance into his life allows him to realize that, yes, he can summon the courage to connect with his fellow animals, realizing his self-worth. Perhaps Dog gives up addressing the accident a little too easily, but the separation of friends has a way of complicating emotions and provoking peculiar reactions.

On occasion, Robot Dreams’ spirit reminds me of Charlie Chaplin’s silent feature film period (1921-1936) – in which Chaplin, at the height of his filmmaking prowess, most successfully wove together slapstick comedy and pathos. On paper, pathos and slapstick should not mix, but Chaplin was the master of combining the two. No wonder Berger fully acknowledges the influence of his favorite Chaplin work, City Lights (1931), here.

Across Robot Dreams, Berger inserts an absurd visual humor that works both because almost all of the characters are animals and despite the fact almost everyone is an animal. A busking octopus in the New York City subway? Check. The image of pigs playing on the beach while sunburnt to a blazing red? You bet. A dancing dream sequence where one of our lead characters finds himself in The Wizard of Oz performing Busby Berkeley-esque choreography on the Yellow Brick Road? Why not? Much of Chaplin’s silent film humor didn’t come from his Little Tramp character, but the silliness, ego, and/or absentmindedness of all those surrounding the Tramp. In City Lights, humor also came from the rough-and-tumble edges of urban America. Such is the case, too, in Robot Dreams, with its blemished, trash-strewn depiction of late ‘80s New York (credit must also go to the sound mix, as they perfectly capture how ambiently noisy a big city can be).

Amid all that comedy, Berger nails the balance between the pathos and the hilarity – pushing too far in either direction would easily undermine the other. The film’s melancholy shows up in ostensibly happy moments and places of recreation: a realization during a rooftop barbeque lunch, the emptiness of a shuttered Coney Island beach in the winter, and an afternoon of kiting in Central Park. It captures how our thoughts of erstwhile or involuntarily separated friends come to us innocuously, in places that stir memories that we might, in our present company, might not speak of aloud.

As the film’s third character, New York City (where Berger lived for a decade) is a global cultural capital, a citywide theater of dreams, a skyscraper-filled signature to the American Dream. To paraphrase Sinatra, if you can make it there, you can make it anywhere. But it tends to grind those dreams into dust. The city’s bureaucratic quagmire is lampooned here, as is its reputation for mean-spirited or jaded locals. Robot Dreams also depicts the visual and socioeconomic differences between the city’s boroughs. With such a jumble of folks of different life stations mashed together, Dog’s people-watching, er, animal-watching during his loneliest moments makes him feel the full intensity of his social isolation. With Robot, however, Dog has a naïve companion that he can show the best of the city to. Robot has no understanding of passive-aggressive or outright hostile behavior (see: Robot hilariously not understanding what a middle finger salute is – the only objectionable scene if you are considering showing this to younger viewers). Within this city of contradictions, Dog and Robot’s love is here to stay.

Though he is no animator, his experience in guiding Spanish actresses Ángela Molina, Maribel Verdú, and Macarena García in Blancanieves through a silent film was valuable. In animated film, there is a tendency towards overexaggerating emotions. But with Robot Dreams’ close adaptation of the graphic novel’s ligne claire style and the nature of Robot’s face, the typical level of exaggeration in animation could not fly in Robot Dreams. Berger and storyboard artist Maca Gil (2022’s My Father’s Dragon, the 2023 Peanuts special One-of-a-Kind Marcie) made few alterations to the storyboards, fully knowing how they wished to frame the film, and hoping to convey the film’s emotions with the facial subtlety seen in the graphic novel. Character designer Daniel Fernandez Casas (Klaus, 2024’s IF) accomplishes this with a minimum of lines to outline characters’ bodies and faces. Meanwhile, art director José Luis Ágreda (2018’s Buñuel in the Labyrinth of the Turtles) and animation director Benoît Féroumont (primarily a graphic novelist) visually translated Sara Varon’s graphic novel using flat colors and a lack of shading to convey background and character depth (one still needs shading, of course, to convey lights and darks of an interior or exterior).

Robot Dreams’ nomination for the Academy Award for Best Animated Feature this year was one of the most pleasant surprises of the 96th Academy Awards.In North America, Robot Dreams’ distributor, Neon, has pursued an inexplicable distribution and marketing strategy of not allowing the film a true theatrical release until months after the end of the last Oscars. The film was available for a one-night special screening in select theaters in and near major North American cities the Wednesday before the Academy Awards. And only now, Neon will release Robot Dreams this weekend in two New York City theaters, the following weekend in and around Los Angeles, with few other locations confirmed – well after interest to watch the film theatrically piqued in North America. Alongside Neon’s near-nonexistent distribution and marketing of Jonas Poher Rasmussen's animated documentary Flee (2021, Denmark), one has to question Neon’s commitment to animated features and whether the company has a genuine interest in showing their animated acquisitions to people outside major North American cities. This is distributional malpractice and maddeningly disrespectful from one of the most acclaimed independent distributors of the last decade.

In Robot Dreams, Pablo Berger and his crew made perhaps the best animated feature of the previous calendar year. Robot Dreams might not have the artistic sumptuousness of the best anime films today, nor the digital polish one expects from the work of a major American animation studio. By film’s end, its simple, accessible style cannot hide its irrepressible emotional power. Its conclusion speaks to all of us who silently wonder about close friends long left to the past, their absence filled only by memory.

My rating: 8.5/10

^ Based on my personal imdb rating. My interpretation of that ratings system can be found in the “Ratings system” page on my blog. Half-points are always rounded down.

For more of my reviews tagged “My Movie Odyssey”, check out the tag of the same name on my blog.

The AI Revolution is Here

By Jan van der Crabben

The image above was not painted by J. M. W. Turner or another 19th century artist, but entirely created by an artificial intelligence (AI) called Midjourney. All I did was to tell the AI to create: “Painting of the Pyramids in Egypt, Turner style, with Nile River and palm trees in the foreground.” It was also entirely free to create it. 

While my AI image of the Pyramids is not perfect, I think that it is a good indication of where we’re going within the next decade. The Great AI Revolution is upon us, and I believe it is going to be of similar historical importance as the invention of the printing press and the Industrial Revolution.

This article is mostly about the future, but it wouldn’t be published here if it wasn’t also about history. So please bear with me while we explore the significance of this moment in history that we inhabit.

I have been thinking about the implications of this for a while (more about that later), but first I want to share a framework with you that has helped me greatly make sense of the historical significance of what’s happening with AI right now. It was developed by Ben Thompson of the Stratechery blog (which I highly recommend to everyone interested in the tech industry). Thompson’s framework  is primarily concerned with creative works such as writing and art, but it can be applied to the production of things, too. He identifies five stages in the production, transmission and consumption chain:

Creation: Having the idea in the first place and working it out.

Substantiation: Turning the idea into reality, such as writing an article or painting an image.

Duplication: Printing the book, newspaper or posters.

Distribution: Getting the finished products to the customer.

Consumption: Allowing the customer to read or purchase the product.

Throughout history, humankind has worked to eliminate bottlenecks in this chain. The invention of writing solved the consumption bottleneck: Before writing, people had to meet in person to exchange (consume) ideas and information. The next great innovation was the invention of the printing press, which solved the problem of duplication as the copying of books became faster by orders of magnitude. Over time, publishers (newspapers in particular) developed better techniques of distribution, aided by the innovations of the Industrial Revolution, such as railroads. However, it was the internet that finally solved the problem of distribution, reducing its cost to zero and putting many newspapers out of business.

This leaves us with two bottlenecks in the transmission chain of ideas: creation and substantiation. While the creation happens in our heads, the substantiation aspect has until now required at least one human to write the article, paint the painting, program the software… you get the idea. That is about to change as artificial intelligence is now able to write and translate texts, create images, read text, transcribe speech, program software, and much more. New applications are being developed at a rapid pace.

I have followed the progress of many of these aspects of computing since the 1990s, and the progress we’ve made in the last 30 years has been stunning! Computer voices used to be robotic, now they are almost human. Today we can give an AI the outline of an article, and it will do an acceptable writing job that requires only some human editing. The images the AI creates are missing key details, but they do convey the desired idea. Things will continue to improve at a rapid pace. 

World History Encyclopedia has particularly benefited from advances in translation. When I first tried computer translation 30 years ago, the result was unreadable. Now, thanks to AI translation, our translation editors are able to review submitted translations in any language, including ones they don’t speak, as we’ve built a system that reverse-translates to English and allows our editors to compare it with the English original paragraph by paragraph. Surely, we may not be able to judge the linguistic quality of the translation, but we can tell if it’s accurate or not. Conversely, our in-house translators can get an English article translated at the click of a button, and all they then need to do is verify and edit the AI translation to bring it up to our standards.

The demand for human translators, artists, writers, data analysts and programmers and other professions is going to drastically decrease over the coming decade, and other jobs will follow suit. In the past, if I had an idea and I couldn’t draw or paint, I could not create the painting. Now, I can ask an AI to do it for me instead.

This will open up possibilities undreamed of and create new jobs that we cannot even imagine yet. To get an idea of what’s already possible, watch this Youtube video where someone explains how he created an entire graphic novel in one day using AI to generate both images and text. Within the next few years, the potential of what we can do with AI will grow exponentially. Google and other companies are already working on AI models that will be able to do more than one thing (e.g. write, paint and speak, not only one at a time) and that will be able to use their existing knowledge to learn new skills more quickly.

That does not mean that humans will have nothing to do. As with the Industrial Revolution, the people who used to do the job will instead be controlling the machines to do the job faster. That is a different skill in itself: While I managed to create images that looked sort of acceptable but not quite right, it is a skill to guide the AI into generating truly beautiful pictures such as this painting of a woman or this painting of a tower. Equally, we would not rely on AI translation for our articles on World History Encyclopedia without having a human review and edit them. AI is a new tool that will help us create things, just like a machine does, but it is still us humans who will need to make it do what we want it to do.

No article about AI would be complete, though, without also mentioning the inherent risks. It is unlikely that the Terminator movies will come true and the AI will rise up against us. A much more real and current issue is related to how AIs are trained using data available on the internet. We all know that the internet contains many bad things that we’d rather get rid of, such as sexism, racism and xenophobia and there is the risk that once AIs are used by everyone, they may inadvertently reinforce the human biases and negative stereotypes.

The rise of AI is also likely to result in staggering improvements to the human condition and if the current trend continues, as I am sure it will, we will see even greater change than people saw during the Industrial Revolution – and it will happen a lot more quickly, too. History is happening in front of our eyes.I thought it would be fitting to end this article with an AI generated image. The prompt I used was: “Workplace of the future.” It looks decidedly retrofuturistic, doesn’t it? Maybe it says more about humanity’s collective thoughts regarding the future than about the AI itself…

The Rise of AI Technology in the Music Industry: Innovation or Threat?

What is it?

The growth of artificial intelligence (AI) technology in the music industry has sparked both interest and concern. This aims to shed light on the intricate relationship between AI technology and the essence of musical creation by taking into account the opinions of musicians, industry professionals, and technology experts. Ultimately, it asks whether AI represents an adverse impact or a harmonious evolution in the music industry, as artificial intelligence or AI technology has played a significant role in the advancement of the music industry in the last few years. As time passes, AI technology are becoming more utilized in every step of the recording, distribution, and listening of music. The controversy whether AI technology is pushing the music industry ahead or a threat to the traditional way of creating music has been raised by the growing integration of AI in the industry.

Artificial Intelligence X Music Collab?

 Traditionally, music production required expensive equipment and a skilled professional to augment the creative process. AI powered tools enable professional ro amateur music producers to freely create professional-sounding tracks with minimal resources. AI can aid in mixing, mastering, and even generate realistic voice recording. This democratization in music production creates a diverse and empowering realm for artists who may have had access to traditional production resources. 

In contrast, the use of AI in music production raises concerns regarding the possibility of decrease of an artist's authenticity. Is it possible for a machine to accurately convey the human feeling through music? According to critics, this could result from an over-reliance on AI, with algorithms prioritizing formulae that are economically successful over the unfiltered, and genuine passion that artists and musicians bring to the table.

While AI can undoubtedly do the whole creative process of creating music, it lacks the essence of human-like touch to it. The raw emotion of musicians embedded in every piece of art that they do is certainly irreplaceable. The challenge for the music industry is to find balance between using AI as a tool for innovation and preserving the authenticity of the art form. 

Conclusion

We agree with using AI technology since it has many advantages and makes our work lives easier. From its efficiency to quality enhancements.

AI technology provides the music industry with a number of advantages, since it can have a significant impact on our careers and open up countless opportunities for us. Similarly, on improving creativity and making it more accessible, as AI transforms the process of making music,.   However, this does not imply that we should be relying on AI technology. It has potential drawbacks as it is made by a robot and not through a human’s passion. For instance, it has no human touch; it lacks emotions. And the dependency on technology leads to the decline of traditional music skills, as trusting in automated works loses the musical intuition of a human produce. The further we go in understanding and learning the pros and cons of AI technology, in the point-of-view of the music industry, it'll leave as a threat, as human passion through music won't be present, as music is known for connecting people to one another emotionally.

Battlecode is MIT’s long-running programming competition. Every January, participants from around the world to write code to program entire armies – not just individual bots – before they duke it out on screen. Throughout Independent Activities Period, participants learn to use artificial intelligence, pathfinding, distributed algorithms, and more to make the best possible team strategy. 👾

Learn more here → https://news.mit.edu/2023/robot-armie...

and here → Battlecode

Top 10 In-Demand Skills for Career Success in 2024

The landscape of employment is in a constant state of flux, shaped by globalization and rapid technological progress. To stay competitive in today’s job market, enhancing skill value is paramount. If you’re curious about the skills that will be in demand for careers in 2024, you’re in the right place.

Let’s delve into some of the most sought-after skills currently and likely to remain crucial in the foreseeable future. Whether you’re a newcomer entering the job market or a seasoned professional aiming to maintain a competitive edge, read on for valuable insights.

Data Science Data science remains a highly sought-after skill, involving the analysis of vast datasets using modern tools and techniques to make informed business decisions. The future of data science looks promising, with its relevance tied to the continuous generation and utilization of data across various industries.

Cloud Computing The demand for cloud engineers and auditors is on the rise as more companies migrate their data to the cloud. Cloud computing encompasses the storage and access of databases, servers, analytics, and other computing services over the internet.

Artificial Intelligence Professionals with expertise in artificial intelligence (AI) are in great demand. AI experts work on machines and tools programmed to emulate human-like thinking. Acquiring AI skills ensures career resilience in the face of market shifts.

DevOps DevOps practices and tools, ensuring a reliable process for creating, testing, and delivering software solutions, are in high demand. This field offers lucrative opportunities, surpassing traditional tech skills in terms of demand.

Full Stack Development Full-stack developers, possessing comprehensive knowledge of both frontend and backend web development, continue to be in high demand across the tech sector. Their versatility and extensive skill set make them valuable assets.

Blockchain Blockchain technology, also known as Distributed Ledger Technology, is expected to see significant growth in the coming years. It involves a decentralized digital ledger recording and distributing transactions across a network of computers.

Robotic Process Automation (RPA) RPA involves the use of technology controlled by organizations for automating routine desk work. This rapidly growing field offers numerous job opportunities as businesses increasingly adopt automation.

AR (Augmented Reality) and VR (Virtual Reality) Extended Reality (XR), including AR and VR, bridges the gap between the real and virtual worlds. As industries embrace XR technology, the demand for experts in this field is expected to rise.

Cybersecurity With the frequency and severity of cyberattacks escalating, cybersecurity skills remain in high demand. The need for professionals adept at safeguarding digital assets is anticipated to grow.

Digital Marketing Businesses across diverse sectors continue to invest in digital marketing to establish a solid presence in their industries. The demand for digital marketing skills remains high and is projected to persist in the coming years.

SilverPeople, a venture by Uberlife Consulting Pvt. Ltd., offers complete recruitment solutions for all hiring/headhunting requirements in a Focused, Accurate, and Time-bound manner (Proprietary FAT* Methodology).

SilverPeople specializes and is placed strongly in 7 Industry verticals: Retail, E-Commerce, Education, Real estate, Fintech, Digital Transformation and Sustainability. SilverPeople has a deep understanding & strong capability to solve Digital Transformation Hiring challenges and is the go-to place for ‘Go Digital’ recruitment consulting!

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