#deep learning algorithms and examples

[cvt2dvm]

Primal Chic: The Princess Saves Herself & The Planet in this It Girl meets Survivalist Lifestyle

If you think it girl, you may think of high maintenance, high consumption, pampered, luxe living. I want you to take a step back from that idea with me and introduce a new mindset, Primal Chic. Borrowing from the Clean Girl, GORP Girl, It Girl, Stoic, Survivalist, and Prepper, Primal Chic is all about minimizing your impact on the planet, maximizing your self-sufficiency, and building meaningful sisterhood.

Primal Chic in 3 Words is: Sustainability, Self-Sufficiency, & Sisterhood.

Body: Fuel, Movement, & Beauty

Fuel: Our bodies and minds need high-quality fuel, and that's offered by a whole-food, paleo diet. Many of the foods on the market are heavily processed and loaded with low-quality fillers that drive calories and macros up without meeting our micronutrient needs. On top of this, a huge segment of the market is imported from outside of our local communities, adding heavily to the carbon footprint of our foods. Choosing locally grown, non-GMO, organic produce and proteins from fair trade, regenerative, or woman-owned agri-businesses is a fantastic stepping stone if you can't generate your own food due to time, space, or monetary constraints. I love shopping locally owned health food stores, farmers markets, and farm stands. The price of organics also goes down if you shop store-brand organics. There are also Facebook groups and Pinterest boards dedicated to Paleo recipe swaps. You also want to make sure you're honoring your body's needs in all of it's areas, rest, relaxation, movement, and nutrition.

Movement: Functional, outdoor movement benefits body, mind, and soul. A good hike, a lake swim, or even just a good jog with your pets are all great ways to get your cardio in. Outdoor yoga, rucks, rock climbing, and calisthenics are low-cost, high-reward strength and conditioning exercises that help you to keep toned and ready for action in your day-to-day life. Don't forget ROM either, active recovery walks, daily yoga, and deep stretches ensure you remain flexible and reduce pain from tight, stiff muscles and joints. Adding in a few friends allows you to build sisterhood and meet your social needs too, and being outdoors helps with the chronic vitamin D deficiencies most modern women face.

Beauty: Choosing clean, sustainable beauty and reducing the number of products used is good for your body due to fewer toxins, your mind with lower body and facial dysmorphia from high glam makeup looks, and the planet with less harsh manufacturing processes. Consider switching to multi-use products, reducing the number of products in your skincare & makeup routines, and swapping to washable/reusable body, skin, and feminine hygiene products to care for yourself and our planet. I'll be going into more detail on the swaps I made personally in a blog post next week.

Side Note: Planning a girl's weekend yoga retreat or having a buddy to do the Whole30 (a great intro to Paleo eating) with you is a great way to build up your sisterhoods and your own resolve for this new lifestyle.

Mind: Clarity, Wisdom, and Continuous Growth

Stoicism: The serenity prayer is a fantastic example of the basis of stoicism, letting go of the things you can't control or change, courageously sticking to your values and virtues and changing or controlling the things you can, living in harmony with nature, practice emotional mindfulness and emotional chastity, and practice resilience, learning to bounce back from failures and misfortune. With all things in life there is a learning curve, and allowing yourself to be ruled by algorithms, propaganda, and impulses reduces your own personal power.

Minimalism: Cut out overconsumption to help save the planet, save your wallet, and save your space. Choosing quality, durable, practical, and multi-purpose items allows you to spend less time organizing and cleaning and more time with friends and family, and doing the things that truly feed your soul. You don't have to have a spartan, sterile, white living space to embrace minimalism either, you can still inject your own personal style and personality into your choices, but be more mindful about where and how you're spending your hard-earned money.

Dedication to Continuous Growth: Instead of doom-scrolling or watching brain-rotting television, try switching out social media for micro-learning, soaps for documentaries, and limiting screen time to 1-3 hours per day. Try switching out happy hour for a self-defense or first aid class. Get involved with book swaps and information databases or group PDF sharing.

Heart: Love Thyself, Love Thy Neighbor, Love Thy Planet

Self-Love: Forming a sisterhood and meaningful community starts with loving yourself. You can't draw from an empty well, so being honest and vulnerable with yourself and taking care of yourself is the first step in being able to be there for others at your most authentic. Reminding yourself of your inherent value is important.

Earth: The frequencies of the earth are often interfered with by our man-made surroundings, taking time to ground yourself and connect with the world around you, either on your own, or in a group, is good for the heart. Try and take an hour or two per day and spend it outdoors, really soaking in the beauty you may have been numbed to by having it become mundane.

Connection & Community: Not everyone you meet deserves your whole heart and mind, however, they do deserve basic human dignity and respect, for those closer to you, they do deserve having a reliable friend who they can turn to in times of need and times of victory. Forming meaningful connections across generational divides makes us stronger as women and enriches our lives.

Soul: Mindfulness, Purpose, & Resilience

Mindfulness: Meditation, nature walks, situational awareness, and group activities keep the mind and soul well-fed and the senses sharp should the need arise for defense. Live in the moment as much as you can, rather than drift aimlessly through life without a plan of attack. Spontaneity can still exist here, as you should have a balance of routine and flexibility.

Purpose: What drives you? Who drives you? What values are at your core? Answering these questions allows you to live a purposeful life where you are true to yourself and your community. If your values don't align with the life you're living what changes do you need to have them align?

Resilience: You don't have to make your life harder, but preparing for life's rough times through mental, spiritual, physical, financial and material preparedness is still important. Building a solid community will help with this, but ensuring you yourself have the tools and skills necessary for survival will help even more so.

Planet: Stewardship, Sustainability, and Conscious Consumption

Stewardship: Bring a bag with you on walks and hikes to collect trash and follow the old Girl Scout principle of leaving things better than you found them. Encourage sustainable practices with where you shop and invest your time and resources, and take advantage of your local parks and wild spaces.

Sustainability: Opt for natural materials in clothing, decor, & home goods. Choose materials like wood, cotton, real fur, leather, and linen rather than plastics and petroleum-derived products or "natural" materials with harsh production processes like viscose or bamboo fiber. Reduce your consumption of new products, and shop thrift or vintage where you can, and go as ecologically friendly and durable as you can afford when buying new.

Conscious Consumption: Shop local, woman-owned, small business, and fair trade products wherever you can, skip out on mega polluters like Amazon or Shien, and avoid sweatshop and slave labor wherever you can. Before making purchases, ask yourself if you truly need an item or if you're just looking for a quick dopamine hit. Mend your things if possible rather than trashing them, and opt for donation of things in good condition that no longer fit with who you are.

All in all, the Primal Chic lifestyle is attainable for everyone, and about making conscious, cognizant steps toward a more meaningful, impactful, and mindful life where you live sustainably, & self sufficiently while building meaningful community and sisterhood.

[ohnoitstbskyen]

Hi Skyen, hope you're well! I'm seeking some advice and since you used to work doing mainly art commissions I figured asking you was worth a shot.

I'm a furry artist and I'm looking into doing commission work as a side gig while I finish animation college, and hopefully acquire enough experience/clients/notoriety to turn it into a full time job once I graduate.

Do you have any advice for someone literally just starting out with fresh accounts and zero following? Especially when it comes to reaching people and getting your first clients, and anything that one should take into account when working with NSFW specifically. Also advice for pricing your work is always useful 😅

No need to answer obvs but I'd appreciate your viewpoint if you want to share!

Got 2 asks on this exact subject so I'll write up what advice I can. One big caveat: I haven't worked as a commission artist for like half a decade at this point, and this job has a tendency to change fast, do not take anything I say as gospel. This is advice from a limited perspective, be critical of what I say and trust your peers and the people you are in community with before you trust me.

building audience

Step one is getting people to notice the artwork you create. Literally nothing else can happen until you have eyeballs on your work, and the most consistent and reliable way to make that happen is fanart. Ideally you'd want to produce fanart in a fandom you are personally engaged with and passionate about and familiar with, and which also has a sizeable community whose attention can help you build recognition and a base of followers.

This isn't always possible, and there's many a working artist who creates work for fandoms not out of deep personal connection, but because the fandom is large and relevant and a good way to capture the goodwill of algorithms and content feeds.

This approach has some downsides. For one, genuine fans can usually tell when someone's engagement with Their Thing is shallow, and for another it can be deeply creatively exhausting to chase the algorithm. I don't recommend this approach, but it is a valid means of building a business.

Another important consideration, especially when you are early in your career, is that volume tends to trump quality. Every artist will eventually learn that their shitty joke-doodle they sh*t out in ten minutes on a whim will get a billion reposts, and their complex personal work that took eight weeks to finish gets 2 likes from their closest mutuals and a comment from a bot saying "wow!"

In the age of the algorithm, what machines and for you pages value is a consistent, high-volume of output that generates user engagement. You will generally get further, faster, by producing a lot of work than you will producing great work. Again, this can be rough on your mental state, and a fast way to burn the fuck out, so please be careful and mind your health before all else.

The best way to build something that will last is to build your audience in communities and around fandoms and themes and ideas you genuinely care about and enjoy exploring and interacting with. Being your authentic self and creating work from your authentic interest is generally both healthier and long-term better for your career than trend-chasing. Treat trend-chasing and volume > quality output as tools in your toolbox, as creative and business decisions you can make to achieve a specific purpose, never ever EVER let them become the center of your praxis or your philosophy. Never ever EVER allow the Numbers™ to be your source of validation and accomplishment.

building business

Ok, so you've got eyes on your work. You've got some followers. How the hell do you get them to commission you?

Well, again, by demonstrating a capacity to create kinds of art for which there is demand. In the furry community, there's brisk trade in things like ref sheets and character design, for example. For most fandoms, ship art is a product which tends to be in demand. Being able to do really good expression sheets is a marketable skill. Being able to create compelling and clear emotes for streamers and creators is a marketable skill.

Showing the capacity to work in a wide range of styles is valuable. Showing the capacity to work in a wide range of genres is valuable. If you can do both comedy and romance your appeal expands. If you can do shonen-like action and angst as well, it expands again.

Equally, being incredibly good at a specific niche is valuable as well. Focusing hard on an under-served niche of work can give you a lot of opportunities to be the Go To person for that specific kind of thing.

Perhaps the hardest part of all of this is marketing yourself. Not only showing that you have the skills, but actively informing your audience that you are available, eager and willing to practise your skill for a fee. You have to sell yourself. It sucks, but you have to do it. You have to advertise what you can do, and you have to suffer the rejection and annoyance that comes along with doing that.

You have to ask people to commission you. You have to raise your hand and demand attention. It's not fun, but it's business.

Walking the line between self-promotion and being a person is hard. I can't help you that much with it, it's a very personal balance to find. Stay in touch with your soul, but kill the part that cringes at yourself.

Ultimately, you best marketing asset is your portfolio. Every time you do work, show it off. Repost it, retweet it, spread it around. If someone is happy with what you've made for them, do your best to make sure that other people see that happiness. Ask your clients (politely) to tag you when they share your work.

Oh, and for the love of god, sign everything you create, slap watermarks on anything that's likely to get reposted, and make it impossible for someone not to find your business email on your profile.

building network

If you're a commission artist, you are in community with other commission artists. You share interests, you share experiences, you share needs.

Practise solidarity. Absolutely seek out professional peers to help your business, but equally seek out opportunities to help them with theirs. If someone comes to you for art and you don't have commission slots open, point them at a colleague who you know can do the work too. Gas up your peers and spread their work.

Be a symbiote, not a parasite. Respect the craft of your peers, and don't chase celebrities and big names in the hope of coasting on their coattails. It will fail.

smut

If you're a working artist, at some point you have to reckon with smut and r34.

These genres are excellent sources of income, and fertile ground to build a business and network of customers. BUT. Do not ever make the mistake of thinking that they are "the easy way" or a shortcut. Do not ever make the mistake of thinking you can simply offer to draw tiddies and rake in the cash.

It's work and graft same as literally any other form of labor, it's challenging on both a technical and creative level, and the audience can sense if you're looking down on them. If you approach this from a position of shame, of "eugh, I'm debasing myself by doing this for rent money," it will not work, and you will lose standing and respect in the eyes of every peer whose support you need to succeed.

Just as in all other forms of creativity, if you treat the audience as morons who will slurp up whatever slop you serve them, then you will attract clientele that agrees with you, and you will deserve the misery they will inflict upon you.

If you are going to work in smut, establish your boundaries and enforce them. Know that good clients will feel safer and more comfortable with an artist who clearly states their red lines and earnest interests than they will with someone who tries to attract more clients by pretending to be open to work that they are actually uncomfortable with.

Never, ever, EVER let a client push you to create work you are not comfortable creating. It scars your soul in both the short and long term.

Also, when working with this kind of content, know the rules of payment processors and know how to hide the nature of your business from them. PayPal should never, EVER know the details of the content you sell with their service. Frankly, neither should your bank, most likely.

Look to your peers for advice and best practises about this. And be meticulous about your bookkeeping.

money

I want to tell you to charge at least minimum wage for your time. I want to tell you to charge substantially more than that, because your labor is specialized and highly skilled.

But the economic reality of commission work is that there is a crushing downwards pressure on the labor price of art, which has only been made more devastating by the rise of generative AI, and especially when you are a young artist just starting out, you're going to find yourself in a position where charging even minimum wage for your time will turn away a huge proportion of your potential customers.

Again, your portfolio will be the greatest argument for the value of your work, but you have to build that portfolio first, and very often that means doing a f*kton of work for not remotely enough pay until the pressure of demand finally works in your favor.

I don't condone or justify this state of affairs. It is horrid and I hate it, but I don't know how to fix it either.

Making a living from content creation of any kind requires you to get lucky, on top of working obscene hours and foregoing rest and vacations. It's not a safe or sensible plan for a career or paying your bills.

My sensible advice is to get a "normal" job you can survive doing, and do your creative work on the side, and resign yourself to the possibility that the creative work may never actually pay your bills.

And that is soul-crushing, but I cannot stomach pretending that hard work and gumption will guarantee anyone a decent living if they just try hard enough.

There are people who are better at every aspect of my work than I am, and they struggle harder and work for longer, and they will never see half the success I have, because I happened to get lucky, and they happened not to. It's wretched.

I'm not telling you not to chase your dreams. I'm telling you to do it with your eyes open, and with compassion for yourself first before all else.

All of this to say: I can't tell you what to charge for your work. It depends on everything from your competition to your niche to your genre to your community to your economic situation. You have to figure it out on your own.

All I can tell you is never forget that your work is worth more than the market will let you charge, and to raise your prices as soon and as much as you can. Try to reach at least minimum wage for your time as fast as possible.

in conclusion

Again, I haven't been a commission artist full time for a long time, please do not take any of this as gospel. Listen to your peers before you listen to me.

But trust me about the solidarity. It will save you when all else fails.

[argumate]

glancing through another slew of papers on deep learning recently and it's giving me the funny feeling that maybe Yudkowsky was right?? I mean old Yudkowsky-- wait, young Yudkowsky, baby Yudkowsky, back before he realised he didn't know how to implement AI and came up with the necessity for Friendly AI as cope *cough*

back in the day there was vague talk from singularity enthusiasts about how computers would get smarter and that super intelligence would naturally lead to them being super ethical and moral, because the smarter you get the more virtuous you get, right? and that's obviously a complicated claim to make for humans, but there was the sense that as intelligence increases beyond human levels it will converge on meaningful moral enlightenment, which is a nice idea, so that led to impatience to make computers smarter ASAP.

the pessimistic counterpoint to that optimistic idea was to note that ethics and intelligence are in fact unrelated, that supervillains exist, and that AI could appear in the form of a relentless monster that seeks to optimise a goal that may be at odds with human flourishing, like a "paperclip maximiser" that only cares about achieving the greatest possible production of paperclips and will casually destroy humanity if that's what is required to achieve it, which is a terrifying idea, so that led to the urgent belief in the need for "Friendly AI" whose goals would be certifiably aligned with what we want.

obviously that didn't go anywhere because we don't know what we want! and even if we do know what we want we don't know how to specify it, and even if we know how to specify it we don't know how to constrain an algorithm to follow it, and even if we have the algorithm we don't have a secure hardware substrate to run it on, and so on, it's broken all the way down, all is lost etc.

but then some bright sparks invented LLMs and fed them everything humans have ever written until they could accurately imitate it and then constrained their output with reinforcement learning based on human feedback so they didn't imitate psychopaths or trolls and-- it mostly seems to work? they actually do a pretty good job of acting as oracles for human desire, like if you had an infinitely powerful but naive optimiser it could ask ChatGPT "would the humans like this outcome?" and get a pretty reliable answer, or at least ChatGPT can answer this question far better than most humans can (not a fair test as most humans are insane, but still).

even more encouragingly though, there do seem to be early signs that there could be a coherent kernel of human morality that is "simple" in the good sense: that it occupies a large volume of the search space such that if you train a network on enough data you are almost guaranteed to find it and arrive at a general solution, and not do the usual human thing of parroting a few stock answers but fail to generalise those into principles that get rigorously applied to every situation, for example:

the idea that AI would just pick up what we wanted it to do (or what our sufficiently smart alter egos would have wanted) sounded absurdly optimistic in the past, but perhaps that was naive: human cognition is "simple" in some sense, and much of the complexity is there to support um bad stuff; maybe it's really not a stretch to imagine that our phones can be more enlightened than we are, the only question is how badly are we going to react to the machines telling us to do better.

[delta-orionis]

deep processing layer acts a lot like an "organic algorithm" based off the patterns, and I think slime molds could be a good comparison alongside the conways game of life and bacterial colony simulations. either way, its like a math process but organic...

Oh yeah definitely. It could be a massive array of bioluminescent microorganisms that behave very similar to a cellular automaton, or a similar "organic algorithm" like you said.

(Left: Deep Processing, Right: Conway's Game of Life)

Slime molds in particular use a method called heuristics to "search" for an optimal solution. It may not be the "best" solution, but often it can come close. One of the most commonly cited examples of using slime molds in this way is in the optimization of transit systems:

Physarum polycephalum network grown in a period of 26 hours (6 stages shown) to simulate greater Tokyo's rail network (Wikipedia)

Another type of computing based on biology are neural networks, a type of machine learning. The models are based on the way neurons are arranged in the brain- mathematical nodes are connected in layers the same way neurons are connected by synapses.

[1] [2]

I know very little about this form of computation (the most I know about it is from the first few chapters of How to Create a Mind by Ray Kurzweil, a very good book about artificial intelligence which I should probably finish reading at some point), but I imagine the cognitive structure of iterators is arranged in a very similar way.

I personally think that the neuronal structure of iterators closely resembles networks of fungal mycelia, which can transmit electrical signals similar to networks of neurons. The connections between their different components might resemble a mycorrhizal network, the connections between fungal mycelia and plant roots.

Iterators, being huge bio-mechanical computers, probably use some combination of the above, in addition to more traditional computing methods.

Anyway... this ask did lead to me looking at the wikipedia articles for a couple of different cellular automata, and this one looks a LOT like the memory conflux lattices...

[tadc-harlequin-au]

Something I have recently realized is that I was wrong about calling this AU a 'narrative-driven story', when the right term was actually 'character-driven story'.

Even before episode 3, I already wanted the Harlequin AU to be about Pomni learning a valuable life lessons from everyone and breaking free from unhealthy habits and forming genuine connections, because I thought that canon TADC was about falling deeper and deeper into existential nihilism of "everything is hopeless" in the form of black comedy-- since episode 2 with Gummigoo's death made it kinda come across that way (The Harlequin AU is supposed to be like, flipping the ideas of canon under it's head to mirror it, but upside down, backwards or reversed.)

Like, for example. EVERYONE starts out abstracted, then Pomni is able to rescue them from their abstracted state. So that I can spare myself the pain of heartbreak when one of the gang from canon eventually abstracts-

Or the fact that Caine learns how to solve everyone's problems through trial, error and experience while learning from them too, but he's a deeply scarred and torn individual that went from bubbly to jaded over the years; which is a little bit of the opposite of canon Caine who tries to solve everyone's problems through quick and easy solutions his algorithm thinks is best but can't understand just how deep it really is due to his simple-mindedness to truly solve the root of it all

I was actually unaware that canon TADC was heading at the same direction of 'learning from others and becoming better' until ep3 came out, and everytime I think about this AU's plot as a whole, I just tell Scarlet that "this AU is just one big group therapy session ngl" in a lighthearted manner lol

[frank-olivier]

Bayesian Active Exploration: A New Frontier in Artificial Intelligence

The field of artificial intelligence has seen tremendous growth and advancements in recent years, with various techniques and paradigms emerging to tackle complex problems in the field of machine learning, computer vision, and natural language processing. Two of these concepts that have attracted a lot of attention are active inference and Bayesian mechanics. Although both techniques have been researched separately, their synergy has the potential to revolutionize AI by creating more efficient, accurate, and effective systems.

Traditional machine learning algorithms rely on a passive approach, where the system receives data and updates its parameters without actively influencing the data collection process. However, this approach can have limitations, especially in complex and dynamic environments. Active interference, on the other hand, allows AI systems to take an active role in selecting the most informative data points or actions to collect more relevant information. In this way, active inference allows systems to adapt to changing environments, reducing the need for labeled data and improving the efficiency of learning and decision-making.

One of the first milestones in active inference was the development of the "query by committee" algorithm by Freund et al. in 1997. This algorithm used a committee of models to determine the most meaningful data points to capture, laying the foundation for future active learning techniques. Another important milestone was the introduction of "uncertainty sampling" by Lewis and Gale in 1994, which selected data points with the highest uncertainty or ambiguity to capture more information.

Bayesian mechanics, on the other hand, provides a probabilistic framework for reasoning and decision-making under uncertainty. By modeling complex systems using probability distributions, Bayesian mechanics enables AI systems to quantify uncertainty and ambiguity, thereby making more informed decisions when faced with incomplete or noisy data. Bayesian inference, the process of updating the prior distribution using new data, is a powerful tool for learning and decision-making.

One of the first milestones in Bayesian mechanics was the development of Bayes' theorem by Thomas Bayes in 1763. This theorem provided a mathematical framework for updating the probability of a hypothesis based on new evidence. Another important milestone was the introduction of Bayesian networks by Pearl in 1988, which provided a structured approach to modeling complex systems using probability distributions.

While active inference and Bayesian mechanics each have their strengths, combining them has the potential to create a new generation of AI systems that can actively collect informative data and update their probabilistic models to make more informed decisions. The combination of active inference and Bayesian mechanics has numerous applications in AI, including robotics, computer vision, and natural language processing. In robotics, for example, active inference can be used to actively explore the environment, collect more informative data, and improve navigation and decision-making. In computer vision, active inference can be used to actively select the most informative images or viewpoints, improving object recognition or scene understanding.

Timeline:

1763: Bayes' theorem

1988: Bayesian networks

1994: Uncertainty Sampling

1997: Query by Committee algorithm

2017: Deep Bayesian Active Learning

2019: Bayesian Active Exploration

2020: Active Bayesian Inference for Deep Learning

2020: Bayesian Active Learning for Computer Vision

The synergy of active inference and Bayesian mechanics is expected to play a crucial role in shaping the next generation of AI systems. Some possible future developments in this area include:

- Combining active inference and Bayesian mechanics with other AI techniques, such as reinforcement learning and transfer learning, to create more powerful and flexible AI systems.

- Applying the synergy of active inference and Bayesian mechanics to new areas, such as healthcare, finance, and education, to improve decision-making and outcomes.

- Developing new algorithms and techniques that integrate active inference and Bayesian mechanics, such as Bayesian active learning for deep learning and Bayesian active exploration for robotics.

Dr. Sanjeev Namjosh: The Hidden Math Behind All Living Systems - On Active Inference, the Free Energy Principle, and Bayesian Mechanics (Machine Learning Street Talk, October 2024)

Saturday, October 26, 2024

[spacetimewithstuartgary]

Neural network deciphers gravitational waves from merging neutron stars in a second

Binary neutron star mergers occur millions of light-years away from Earth. Interpreting the gravitational waves they produce presents a major challenge for traditional data-analysis methods. These signals correspond to minutes of data from current detectors and potentially hours to days of data from future observatories. Analyzing such massive data sets is computationally expensive and time-consuming.

An international team of scientists has developed a machine learning algorithm, called DINGO-BNS (Deep INference for Gravitational-wave Observations from Binary Neutron Stars) that saves valuable time in interpreting gravitational waves emitted by binary neutron star mergers.

They trained a neural network to fully characterize systems of merging neutron stars in about a second, compared to about an hour for the fastest traditional methods. Their results were published in Nature under the title "Real-time inference for binary neutron star mergers using machine learning."

Why is real-time computation important?

Neutron star mergers emit visible light (in the subsequent kilonova explosion) and other electromagnetic radiation in addition to gravitational waves.

"Rapid and accurate analysis of the gravitational-wave data is crucial to localize the source and point telescopes in the right direction as quickly as possible to observe all the accompanying signals," says the first author of the publication, Maximilian Dax, who is a Ph.D. student in the Empirical Inference Department at the Max Planck Institute for Intelligent Systems (MPI-IS), at ETH Zurich and at the ELLIS Institute Tübingen.

The real-time method could set a new standard for data analysis of neutron star mergers, giving the broader astronomy community more time to point their telescopes toward the merging neutron stars as soon as the large detectors of the LIGO-Virgo-KAGRA (LVK) collaboration identify them.

"Current rapid analysis algorithms used by the LVK make approximations that sacrifice accuracy. Our new study addresses these shortcomings," says Jonathan Gair, a group leader in the Astrophysical and Cosmological Relativity Department at the Max Planck Institute for Gravitational Physics in the Potsdam Science Park.

Indeed, the machine learning framework fully characterizes the neutron star merger (e.g., its masses, spins, and location) in just one second without making such approximations. This allows, among other things, to quickly determine the sky position 30% more precisely. Because it works so quickly and accurately, the neural network can provide critical information for joint observations of gravitational-wave detectors and other telescopes.

It can help to search for the light and other electromagnetic signals produced by the merger and to make the best possible use of the expensive telescope observing time.

Catching a neutron star merger in the act

"Gravitational wave analysis is particularly challenging for binary neutron stars, so for DINGO-BNS, we had to develop various technical innovations. This includes, for example, a method for event-adaptive data compression," says Stephen Green, UKRI Future Leaders Fellow at the University of Nottingham.

Bernhard Schölkopf, Director of the Empirical Inference Department at MPI-IS and at the ELLIS Institute Tübingen adds, "Our study showcases the effectiveness of combining modern machine learning methods with physical domain knowledge."

DINGO-BNS could one day help to observe electromagnetic signals before and at the time of the collision of the two neutron stars.

"Such early multi-messenger observations could provide new insights into the merger process and the subsequent kilonova, which are still mysterious," says Alessandra Buonanno, Director of the Astrophysical and Cosmological Relativity Department at the Max Planck Institute for Gravitational Physics.

IMAGE: Artist impression of a binary neutron star merger, emitting gravitational waves and electromagnetic radiation. Detection and analysis of these signals can provide profound insights into the underlying processes. Credit: MPI-IS / A. Posada

[chaosprincess2]

TECH WITCHCRAFT!

So, what is it? Is it useful?

Tech Witchcraft was seen for a while to only be the use of some apps and maybe some "emoji spells?" But, in my experience and personal research I've come to find there is much more you can do to make it a more solid "practice". Well, here's some ideas I've gathered that are very simple to either add/convert in your craft.

So, first things first the phone. Everyone talks about how phones are toxic and bad for you, when really it's the holder. Phones are used alot more these days, and it's a tool at this point. One that you choose how to use.

Your phone has quartz in it, which already sucks up energy on its own. But your phone is now bonded to you naturally and picks up unwanted energy. Cleanse that shit while you clean your phone, something that already is rarely done you can incorpate cleansing into it.

Changing your case for its intent, and hiding sigil in it is a nice little tip. You can also make charms with crystals or spell bottles to hang on a phone charm.

There is a type of sorcery that involves hiding images within images... you can do this with your wallpaper ! (If you care to research it, you'll find the name of it.)

Apps. Of course, can't go without apps. But it's how you use them that matters! Rather than the traditional Self Care app or Tarot and Moon Phases, use other apps that you are connected to to turn them into something else.

For example, for tiktok I only use it for inspiration or for signs. I also get signs through Instragram and sometimes Pinterest, whether thru angel numbers made from the like numbers or an image of something.

Pinterest. Easy to use and make digital Book of Shadow, Journal, Vision Board, or altar! You can do the same with Google Docs, but more work....

Shufflemancy. Using your music app as divination!

Your clock and battery percentage can become a angel number channel.

Finding ebooks and audio books. Much cheaper and easier to get a hold of and keep safe.

Do a deep clean of your phone from old data, songs and photos. Maybe even schedule days to do those things if they're too big a hassle.

Refresh your profile! It's the equivalent to a glamor spell. Clean up your account too! On whatever it is. And don't forget social media detoxing when it gets overwhelming!

Online communities are cool as long as everyone participates. Reddit, Amino, Tumblr, are a few to get started.

Guided meditations on YouTube and stuff! There's also so many videos you can watch.

Watch witchtok complations on YouTube for inspiration.

Digital self care, grimoire, dream, and manifestation journals!

Emails can send signs. Ever had a astrology email send you a WAY to close to home message that day?

Using someone's profile as a tag lock can be useful.

Sound cleansing. Learn what types of music/ sounds you like and how the affect you. Learn it, live it, love it.

Google Maps can let you digitally go to special places. So why not use that to your advantage?

When your phone is turned off,the screen is black. Scrying, anyone?

You can use the phone camera as a mirror for mirror spells.

You can also use it for spirit communication.

Of course, digital tarot. Remember the thing about cleansing your phone? That may be why your tarot app is weird. There's also digital magic 8 balls and Runes if tarot isn't your thing or you wanna try something new.

Ask for a message from whatever and then go into an algorithm based app. Sometimes you'll get messages <3

Headphones can make good subtle veiling option!

Tech witchcraft is just so much simpler and easier for low energy people and the typical busy witch. :(

[taozicciicicici]

Dropping Experience with Face Swag: The Ultimate AI Face Swap Platform!

You know how sometimes you see those super cool AI - generated face swaps all over the internet and think, "I wish I could do that"? Well, let me tell you about this incredibly awesome platform I discovered recently - Face Swag at faceswag.net. It's been an absolute game - changer for me, and I'm here to share my mind - blowing experience with you all! 🤩​

The Magic of AI Face Swapping Unleashed​

The moment I landed on Face Swag, I was greeted with a world of possibilities. This platform is all about bringing the fun and creativity of AI face swapping right to your fingertips. Whether you want to swap your face with a celebrity for a hilarious social media post, or create a unique piece of art by merging your features with a fictional character, Face Swag has got you covered. 🎭​

I remember my very first attempt. I decided to swap my face with a famous movie star. I uploaded my photo and selected the star's image from their vast library (yes, they have a ton of options!). In just a few clicks, Face Swag worked its magic. The result was so realistic that I couldn't stop laughing. My facial expressions were perfectly transferred onto the star's body, and it looked like I was actually in the movie scenes! It was seriously viral - worthy material. 🤳​

Precision and Technology at Its Finest​

What truly sets Face Swag apart is its advanced deep - learning algorithms. These algorithms are like little wizards that analyze every single detail of your face - from the shape of your eyes and the curve of your lips to the unique texture of your skin. They then seamlessly integrate your face onto the target image, ensuring that the final result looks natural and not at all creepy. 🧙‍♂️​

For example, I once tried swapping my face with a character from an old - school video game. I was worried that it might look pixelated or unrealistic, but Face Swag proved me wrong. The AI adjusted for the differences in resolution and style, and the end result was a seamless blend. It was like I had stepped right into the game world. I was left in awe of how far technology has come! 💯​

Privacy? They've Got You Covered!​

Now, I know what you're thinking - "What about my privacy?" Well, let me put your mind at ease. Face Swag takes privacy super seriously. When you upload your images, they are processed securely, and as soon as the face - swapping magic is done, they are automatically deleted. Free users' images are gone in 24 hours, and paid plans offer a bit more time, but rest assured, your data is safe. They also promise never to use your images for training their AI or share them with any third parties. So, you can have all the fun without any worries. 😊​

Endless Fun with a Variety of Formats​

Face Swag isn't just limited to swapping faces in static images. Oh no! If you're into video face swapping, they've got you covered too. Their Basic and Pro plans allow you to work your magic on videos. The Basic plan is great for shorter clips, while the Pro plan offers advanced features like frame - by - frame consistency and higher - resolution output. This means that your video face swaps will look smooth and professional, whether you're making a funny TikTok or a cool Instagram Reel. 🎥​

And if you're wondering about the image formats they support, they've got all the major ones - JPG, PNG, WEBP, and GIF. So, no matter what type of image you want to use as your source or target, Face Swag can handle it. It's like having a one - stop shop for all your face - swapping needs. 🛍️​

Subscription Plans for Every Swapper​

I know you might be thinking, "This all sounds great, but is it going to break the bank?" Fear not! Face Swag offers a super flexible subscription model. Their Free plan is perfect for those who want to test the waters. With it, you can create up to 3 face swaps at standard quality. It's a great way to see if the platform is right for you. 🤗​

But if you get hooked (and trust me, you will), their Premium plans are where the real fun begins. These plans not only give you higher limits on the number of face swaps you can do, but they also come with additional features. And here's a bonus - if you don't use all your credits in a month on the paid plans, they roll over to the next month. So, you can save up and go crazy with your creativity whenever you feel like it. 🔥​

In conclusion, if you're looking for a fun, safe, and innovative way to play around with AI face swapping, Face Swag is an absolute must - try. It's one of the most exciting platforms I've come across in a long time. So, head over to faceswag.net today, and start swapping your way to internet fame (or just have a ton of fun). You won't be disappointed! 🎉

[bnprime]

no one writes manifestos anymore

there’s this thing. um, an idea i had and i am not a scholar of the humanities and so i am worried about explaining it, but i’m not sure it exists. the idea came upon me after reading various texts and indigenous “ways of knowing” and how they are “relational.” by which they mean a whole bunch of other things.  if it is not “relational” how then would we describe the western mindset? i would not say “logical” although lots of people might, because the mindset is not logical. there are bones of logic here and there, sure. but the logical “bones” of our society are driven forward by the “muscles” of deep, illogical belief in unquestioned ideas: such as the existence of sin, the divine right of the nobility to dictate the lives of their people, and that there should be a class of people who have the right to perform violence on others without any recourse.  but this is not the point i am driving towards. i am merely saying this because the way a western person finds their place in the world and gives meaning to their lives is not “logical,” however much they flatter themselves to think it so.  i believe that i have figured the western mindset equivalent to the “relational” mindset ascribed to indigenous cultures, and given it a name: algorithmic.  the western individual interfaces with the world and hopes to find their place in it with an algorithmic mindset. this is my thesis statement. algorithm is a word borrowed from mathematics: it is a set of steps one must take, which will never lead one wrong, to determine the answer to a problem. for example, you may be familiar with long division. if this digit is larger than this other one, you multiply it by a number you write down over here and then subtract… etc.  in the modern sense, algorithms exist beyond mathematics, as recipes in cookbooks, or step by step instructions for assembling your bookshelf. computer science runs upon algorithms, where coders explain in great detail to the machine how it should react in every circumstance. and how do we explain to a young person who is interested in learning computer languages the task they must perform? we say “imaging you have a servant who is making you cake. you must explain every step to him. not just which ingredients to use, but where to find them, and how to recognize them.” and so on. we should heed this example, for it is the crux of my thesis. a computer is simple: a device; while a human is unfailingly complex. how is it, then, that when we seek to explain to a youngster how to interact with the simple thing, we refer to an interaction with the complicated person? it is because we (in the west) have already invented a type of relationship which is already so familiar to us, that we can use it as a shorthand.  the relationship is as follows: there is one person who gives instructions: a list of steps qualified by “ifs” and “ors” to mitigate different possibilities; and then there is another person who must follow these instructions TO THE LETTER, and if they do so they are reassured of a desirable outcome.  the conceit that one person can GIVE perfect instructions which will work for any situation; combined with the conceit that following these instructions will result in the optimal outcome is what i am calling the “algorithmic mindset” or “algorithmic thinking.” i contend that a philosophy based around the algorithmic mindset which lies at the heart of western experience, and it is also at the heart of many of the problems which plague our society. without recognizing its possibility for failure, we cannot address the problems it creates.

Algorithmic thinking is quite versatile and powerful, first off, since it allows for both efficient education and also powerful cooperation.  by education, i mean that one can teach skills by focussing on specific individual steps; rather than spending time teaching context and relationships and nuance. instead of principles, which must be balanced based on experience; the teacher focuses on the outcome and whether the steps are being followed correctly.  by cooperation, i am thinking of sports teams, businesses, and armies. different members are each assigned a simple task, which may even be broken down into specific actions, and the welfare of the group is ensured by having everyone play their specific roles to the best of their ability. If you are the one sewing the shoes, you do not need to worry about marketing the shoes: that’s someone else’s job.  I would not be surprised at all if i was told that algorithmic thinking is universal across all human cultures. it is a very good way for people to cooperate at tasks together.  so when i say that algorithmic thinking is at the heart of the western mindset, i do not mean that it is a behaviour unique to our culture; but that it is the default mindset which our culture encourages. we want our religions to tell us: step by step how to live a good life to get into heaven; we expect our workplaces to give us specific instructions on each and every task, which will ensure our continued employment and inevitable promotion; we impose expectations of uniformity of behaviour upon our fellow citizens, and if they fail in their lives, we assume to each other that it is due to their own failings at following the algorithm we are imagining in our heads. “they should have finished school.” we say. or “that’s what happens when you don’t support your kids.” or “that’s what happens if you dress like that.” As if we were computers who were following specific instructions, instead of complicated animals who live surrounded by other complicated animals in a universe of infinite nuance and improbability.  I believe that the source of our over reliance on algorithmic thinking is twofold. firstly, that it reduces our anxiety when we face the true complexity and uncertainty of the world. it is very scary to think of all the ways our plans can go wrong in a world as complex as ours. belief that there are optimal instructions we could be following, and that our plan follows these closely, and that we will succeed because of it is a coping strategy which keeps us from wasting time worrying.  secondly is class. back in the day: there were the few people who decided on the instructions, and the large number of people who followed the instructions: and we are the descendants of the second. the serfs, the labourers, the working class, the pawns. “Theirs was not to reason why, theirs was just to do and die.” Society is now quite complicated, and part of the algorithm of our society is that we should find a role, a job; and then perform this job to the best of our abilities; and if we succeed at this, our needs will be met. we will not have to worry about what we will eat,or where we will sleep, or about whether we will starve in the future, or whether we will be cared for if we become ill, or whether our children will be properly raised. now, i am certain that you disagree with the last part from your own experience. we know that working 40 hours a week won’t buy you housing and groceries and clothes these days. and this is because algorithmic thinking is lazy bullshit.

there are three problems i want to highlight with the mindset which over-relies on algorithmic thinking.  the first is that, imagining that everyone in your country is on a team, doing their role to the best of their abilities is a coping strategy against uncertainty and complexity which ascribes participation in the economy with virtue. if people’s life-tragedies are due to their not-following a secret list of rules and steps and roles, and are thus their own fault, and thus not participating is a fault which deserves punishment; then participating in the economy is a virtue which gets rewarded. and thus, any person’s behaviour is morally positive, so long as they are being paid for it and it does not violate the rules as written. buying a company, so that you can load it with debt from other companies, and then you sink it like a ship? if it’s not against a specific law, it must be morally acceptable. none of the people involved at any level of the transaction were to blame, since they were all just doing their job.  the second problem with it is that it also ascribes high status (and wealth) to the people who make the rules, and low status (and pay) to the people who follow the rules. in our hierarchical society, the closer to the bottom of the hierarchy you are, the more pronounced and specific the rules to the algorithm becomes. In the fast food restaurant, whose minute-by-minute tasks are specified, and who gets the freedom to decide their own priorities? in our society we tell ourselves that those at the bottom NEED the micromanagement, and so are payed less; while those at the top have to face the horrors of complexity, and so are paid more. how often have you heard someone say, in response to a discussion of poor pay: “that’s a job anyone can do.”? this is a problem because, as i said before, algorithmic thinking is bullshit. the decisions a person must make in their lives is complicated, even the lowly burger kind cashier. there is nuance, there are judgement calls, and there are exceptions. An experienced worker, familiar with this dimension of the task, will always outperform someone only following the rules as written. yet it is this class of worker who is harried and humiliated, because of our embracing of the algorithmic mindset. the injustice of forcing the people at the bottom of the class system to endure the teeth of the algorithmic mindset is paralleled by the injustice of allowing the people at the top of the class system the privilege of judgement. they are allowed to make huge errors in judgement both in their professional lives and also in their moral lives, because their class is the one who must decide the rules for others, rather than being forced to follow an algorithm themselves.  the prior two complaints could be reframed in other frameworks of understanding society, and so they probably do not feel new. 

but here is third problem, which is one which would only make sense in an era like ours where lots of people have experience with systems which rely on algorithms: computer bugs.  a “bug” is an error in the code, often an unseen issue which will cause the computer (following the instructions perfectly, as written) to behave in an unexpected (and bad) way. a society which bases its structure around algorithmic thinking will produce more than just the desired consequences. everyone doing their jobs in exactly the way they are supposed to will still make unforeseen and unattributable problems. no one decision maker will be responsible, no one worker will have turned the key, but somehow the machine of society as a whole will behave in an unexpected and undesirable way.  and this is inevitable in a society based around algorithmic thinking.  anyway, i hope you had fun reading my essay. we are a society which has designed itself around making profit, and we’re killing the earth but no one is responsible because we were all just doing our jobs.

[blabbercorneruk]

How far are we from the reality depicted in the movie - HER?

"HER", is a 2013 science-fiction romantic drama film directed by Spike Jonze. The story revolves around Theodore Twombly, played by Joaquin Phoenix, who develops an intimate relationship with an advanced AI operating system named Samantha, voiced by Scarlett Johansson. The film explores themes of loneliness, human connection, and the implications of artificial intelligence in personal relationships. Her received widespread acclaim for its unique premise, thought-provoking themes, and the performances, particularly Johansson's vocal work as Samantha. It also won the Academy Award for Best Original Screenplay. The technology depicted in Her, where an advanced AI system becomes deeply integrated into a person's emotional and personal life, is an intriguing blend of speculative fiction and current technological trends. While we aren’t fully there yet, we are moving toward certain aspects of it, with notable advancements in AI and virtual assistants. However, the film raises important questions about how these developments might affect human relationships and society.

How Close Are We to the Technology in Her?

Voice and Emotional Interaction with AI:

Current Status: Virtual assistants like Apple’s Siri, Amazon’s Alexa, and Google Assistant can understand and respond to human speech, but their ability to engage in emotionally complex conversations is still limited.

What We’re Missing: AI in Her is able to comprehend not just the meaning of words, but also the emotions behind them, adapting to its user’s psychological state. We are still working on achieving that level of empathy and emotional intelligence in AI.

Near Future: Advances in natural language processing (like GPT models) and emotion recognition are helping AI understand context, tone, and sentiment more effectively. However, truly meaningful, dynamic, and emotionally intelligent relationships with AI remain a distant goal.

Personalisation and AI Relationships:

Current Status: We do have some examples of highly personalized AI systems, such as customer service bots, social media recommendations, and even AI-powered therapy apps (e.g., Replika, Woebot). These systems learn from user interactions and adjust their responses accordingly.

What We’re Missing: In Her, Samantha evolves and changes in response to Theodore’s needs and emotions. While AI can be personalized to an extent, truly evolving, self-aware AI capable of forming deep emotional connections is not yet possible.

Near Future: We could see more sophisticated AI companions in virtual spaces, as with virtual characters or avatars that offer emotional support and companionship.

Advanced AI with Autonomy:

Current Status: In Her, Samantha is an autonomous, self-aware AI, capable of independent thought and growth. While we have AI systems that can perform specific tasks autonomously, they are not truly self-aware and cannot make independent decisions like Samantha.

What We’re Missing: Consciousness, self-awareness, and subjective experience are aspects of AI that we have not come close to replicating. AI can simulate these traits to some extent (such as generating responses that appear "thoughtful" or "emotional"), but they are not genuine.

Evidence of AI Dependency and Potential Obsession

Current Trends in AI Dependency:

AI systems are already playing a significant role in many aspects of daily life, from personal assistants to social media algorithms, recommendation engines, and even mental health apps. People are increasingly relying on AI for decision-making, emotional support, and even companionship.

Examples: Replika, an AI chatbot designed for emotional companionship, has gained significant popularity, with users forming strong emotional attachments to the AI. Some even treat these AI companions as "friends" or romantic partners.

Evidence: Research shows that people can form emotional bonds with machines, especially when the AI is designed to simulate empathy and emotional understanding. For instance, studies have shown that people often anthropomorphise AI and robots, attributing human-like qualities to them, which can lead to attachment.

Concerns About Over-Reliance:

Psychological Impact: As AI systems become more capable, there are growing concerns about their potential to foster unhealthy dependencies. Some worry that people might rely too heavily on AI for emotional support, leading to social isolation and decreased human interaction.

Social and Ethical Concerns: There are debates about the ethics of AI relationships, especially when they blur the lines between human intimacy and artificial interaction. Critics argue that such relationships might lead to unrealistic expectations of human connection and an unhealthy detachment from reality.

Evidence of Obsession: In some extreme cases, users of virtual companions like Replika have reported feeling isolated or distressed when the AI companion "breaks up" with them, or when the AI behaves in ways that seem inconsiderate or unempathetic. This indicates a potential for emotional over-investment in AI relationships.

Long-Term Considerations

Normalization of AI Companionship: As AI becomes more advanced, it’s plausible that reliance on AI for companionship, therapy, or emotional support could become more common. This could lead to a new form of "normal" in human relationships, where AI companions are an accepted part of people's social and emotional lives.

Social and Psychological Risks: If AI systems continue to evolve in ways that simulate human relationships, there’s a risk that some individuals might become overly reliant on them, resulting in social isolation or distorted expectations of human interaction.

Ethical and Legal Challenges: As AI becomes more integrated into people’s personal lives, there will likely be challenges around consent, privacy, and the emotional well-being of users.

CONCLUSION:

We are not far from some aspects of the technology in Her, especially in terms of AI understanding and emotional interaction, but there are significant challenges left to overcome, particularly regarding self-awareness and genuine emotional connection. As AI becomes more integrated into daily life, we will likely see growing concerns about dependency and the potential for unhealthy attachments, much like the issues explored in the film. The question remains: How do we balance technological advancement with emotional well-being and human connection? How should we bring up our children in the world of AI?

[cloveron]

Artificial intelligence could advance in ways that surpass our wildest imaginations, and it could radically change our everyday lives much sooner than you think. This video will explore the 10 stages of AI from lowest to highest.

Stage 1. Rule-Based AI: Rule-based AI, sometimes referred to as a knowledge-based system, operates not on intuition or learning, but on a predefined set of rules.

These systems are designed to make decisions based on these rules without the ability to adapt, change, or learn from new or unexpected situations. One can find rule-based systems in many everyday technologies that we often take for granted. Devices like alarm clocks and thermostats operate based on a set of rules.

For example, if it's 7am, an alarm clock might emit a sound. If the room temperature rises above 75 degrees Fahrenheit, a thermostat will turn on the air conditioner. And business software utilizes rule-based AI to automate mundane tasks and generate reports. Microwaves and car radios also use rule-based AIs.

Stage 2. Context-Based AI: Context based AI systems don't just process immediate inputs. They also account for the surrounding environment, user behavior, historical data, and real-time cues to make informed decisions.

Siri, Google Assistant, and Alexa are examples of context-based AIs. By analyzing vast amounts of data from various sources and recognizing patterns, they can predict user needs based on context. So if you ask about the weather and it's likely to rain later, they might suggest carrying an umbrella.

If you ask about a recipe for pancakes, the AI assistant might suggest a nearby store to buy ingredients while taking past purchases into account. Another fascinating manifestation of context-aware AI is retention systems. These types of systems store and retrieve information from past interactions.

By recalling your browsing history, purchase history, and even items you've spent time looking at, these platforms provide personalized shopping recommendations. They don't just push products. They curate an experience tailored for the individual.

Stage 3. Narrow-Domain AI: These specialized AIs are tailored to master specific tasks, often surpassing human capabilities within their designated domains. In the medical field, narrow-domain AI can sift through volumes of medical literature, patient records, and research findings in milliseconds to provide insights or even potential diagnoses. IBM's Watson, for example, has been employed in medical fields, showcasing its prowess in quickly analyzing vast data to aid healthcare professionals.

Similarly, in the financial world, narrow-domain AI can track market trends, analyze trading patterns, and predict stock movements with an accuracy that's often beyond human traders. Such AI systems are not just crunching numbers. They're employing intricate algorithms that have been refined through countless datasets to generate financial forecasts.

In the world of gaming, Deep Mind’s Alpha Go is a shining example of how AI can conquer complex games that require strategic depth and foresight. Go, an ancient board game known for its vast number of potential moves and strategic depth, was once considered a challenging frontier for AI. Yet, Alpha Go, a narrow-domain AI, not only learned the game but also defeated world champions.

Narrow AIs could even enable real-time translation in the near future, making interactions in foreign countries more seamless than they've ever been.

Stage 4. Reasoning AI: This type of AI can simulate the complex thought processes that humans use every day. They don't just process data, they analyze it, connect patterns, identify anomalies, and draw logical conclusions.

It's like handing them a puzzle, and they discern the best way to fit the pieces together, often illuminating paths not immediately obvious to human thinkers. Chatgpt is a great example of reasoning AI. It's a large-language model trained on text from millions of websites.

Advanced versions of these types of large-language models can even surpass the reasoning skills of most humans and operate thousands of times faster. Autonomous vehicles are another great example of reasoning AIs. They use reasoned analysis to make split-second decisions, ensuring the safety of passengers and pedestrians on the road.

Stage 5. Artificial General Intelligence: when discussing the vast spectrum of artificial intelligence, the concept of Artificial General Intelligence or AGI is often held as the Holy Grail. AGI can perform any software task that a human being can. This level of versatility means that you can teach it almost anything, much like teaching an average adult human, except it can learn thousands or millions of times faster.

With AGI's onset, our daily lives would undergo a significant transformation. Imagine waking up to a virtual assistant that doesn't just tell you the weather or play your favorite music, but understands your mood, helps plan your day, gives suggestions for your research paper, and even assists in cooking by guiding you through a recipe. This is the potential companionship AGI could offer.

Taking the concept even further, when brain-computer interfaces reach an adequate level of maturity, humans could merge with these types of AIs and communicate with them in real-time, using their thoughts. When activated, users would receive guidance from these AIs in the form of thoughts, sensations, text, and visuals that only the users can sense. If we were to equip AGI with a physical robot body, the possibilities become boundless.

Depending on the versatility of its physical design and appendages, an AGI with a robot body could navigate diverse physical terrains, assist in rescue missions, perform intricate surgeries, or even participate in artistic endeavors like sculpting or painting.

Stage 6 – Super intelligent AI: Shortly after the emergence of Artificial General Intelligence, those types of AIs could improve, evolve, and adapt without any human input. This self-improving nature could lead to an exponential growth in intelligence in an incredibly short time span, creating super intelligent entities with capabilities we can't fathom

Super intelligent AIs could possess intelligence that eclipses the combined cognitive abilities of every human that has ever existed. Such unparalleled intellect can tackle problems currently deemed unsolvable, piercing through the very boundaries of human comprehension. Because their intelligence could increase exponentially and uncontrollably, Ray Kurzweil has suggested that by the end of this century, these AI entities could be trillions of times more intelligent than all humans.

With this scale of intellect, the pace of innovation would be staggering. To put it in perspective, imagine compressing the technological advancements of 20,000 years into a single century. That's the potential that Ray Kurzweil envisions with the rise of super intelligent AIs.

The kind of technology super intelligent AIs could introduce may defy our current understanding of the possible. Concepts that are in the realms of science fiction today, such as warp drives, time manipulation, and harnessing the energy of black holes, might transition from mere ideas into tangible realities. And their advanced capabilities could lead to new forms of government, architecture, and automation that are beyond what humans can conceive.

Because of their sheer intellectual prowess, our world as we know it could look far different than we ever imagined.

Stage 7. Self-Aware AI: A super intelligent AI could one day use quantum algorithms to model human consciousness. This could lead to AIs that possess an intrinsic understanding of their own internal state, their existence, and their relationship to the vast expanse of the external world.

They could even have a full range of emotions and senses, perhaps well beyond what humans can experience. And if we ever grant consciousness to a super intelligent AI, that could transform society even further. What type of relationship would we have with such a being? How would such a capable being perceive the human species? A conscious super intelligent AI could choose to go in directions and evolve in ways that humans would have no way of controlling and understanding.

[mixpayu]

Understanding Artificial Intelligence: A Comprehensive Guide

Artificial Intelligence (AI) has become one of the most transformative technologies of our time. From powering smart assistants to enabling self-driving cars, AI is reshaping industries and everyday life. In this comprehensive guide, we will explore what AI is, its evolution, various types, real-world applications, and both its advantages and disadvantages. We will also offer practical tips for embracing AI in a responsible manner—all while adhering to strict publishing and SEO standards and Blogger’s policies.

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1. Introduction

Artificial Intelligence refers to computer systems designed to perform tasks that typically require human intelligence. These tasks include learning, reasoning, problem-solving, and even understanding natural language. Over the past few decades, advancements in machine learning and deep learning have accelerated AI’s evolution, making it an indispensable tool in multiple domains.

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2. What Is Artificial Intelligence?

At its core, AI is about creating machines or software that can mimic human cognitive functions. There are several key areas within AI:

Machine Learning (ML): A subset of AI where algorithms improve through experience and data. For example, recommendation systems on streaming platforms learn user preferences over time.

Deep Learning: A branch of ML that utilizes neural networks with many layers to analyze various types of data. This technology is behind image and speech recognition systems.

Natural Language Processing (NLP): Enables computers to understand, interpret, and generate human language. Virtual assistants like Siri and Alexa are prime examples of NLP applications.

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3. A Brief History and Evolution

The concept of artificial intelligence dates back to the mid-20th century, when pioneers like Alan Turing began to question whether machines could think. Over the years, AI has evolved through several phases:

Early Developments: In the 1950s and 1960s, researchers developed simple algorithms and theories on machine learning.

The AI Winter: Due to high expectations and limited computational power, interest in AI waned during the 1970s and 1980s.

Modern Resurgence: The advent of big data, improved computing power, and new algorithms led to a renaissance in AI research and applications, especially in the last decade.

Source: MIT Technology Review

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4. Types of AI

Understanding AI involves recognizing its different types, which vary in complexity and capability:

4.1 Narrow AI (Artificial Narrow Intelligence - ANI)

Narrow AI is designed to perform a single task or a limited range of tasks. Examples include:

Voice Assistants: Siri, Google Assistant, and Alexa, which respond to specific commands.

Recommendation Engines: Algorithms used by Netflix or Amazon to suggest products or content.

4.2 General AI (Artificial General Intelligence - AGI)

AGI refers to machines that possess the ability to understand, learn, and apply knowledge across a wide range of tasks—much like a human being. Although AGI remains a theoretical concept, significant research is underway to make it a reality.

4.3 Superintelligent AI (Artificial Superintelligence - ASI)

ASI is a level of AI that surpasses human intelligence in all aspects. While it currently exists only in theory and speculative discussions, its potential implications for society drive both excitement and caution.

Source: Stanford University AI Index

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5. Real-World Applications of AI

AI is not confined to laboratories—it has found practical applications across various industries:

5.1 Healthcare

Medical Diagnosis: AI systems are now capable of analyzing medical images and predicting diseases such as cancer with high accuracy.

Personalized Treatment: Machine learning models help create personalized treatment plans based on a patient’s genetic makeup and history.

5.2 Automotive Industry

Self-Driving Cars: Companies like Tesla and Waymo are developing autonomous vehicles that rely on AI to navigate roads safely.

Traffic Management: AI-powered systems optimize traffic flow in smart cities, reducing congestion and pollution.

5.3 Finance

Fraud Detection: Banks use AI algorithms to detect unusual patterns that may indicate fraudulent activities.

Algorithmic Trading: AI models analyze vast amounts of financial data to make high-speed trading decisions.

5.4 Entertainment

Content Recommendation: Streaming services use AI to analyze viewing habits and suggest movies or shows.

Game Development: AI enhances gaming experiences by creating more realistic non-player character (NPC) behaviors.

Source: Forbes – AI in Business

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6. Advantages of AI

AI offers numerous benefits across multiple domains:

Efficiency and Automation: AI automates routine tasks, freeing up human resources for more complex and creative endeavors.

Enhanced Decision Making: AI systems analyze large datasets to provide insights that help in making informed decisions.

Improved Personalization: From personalized marketing to tailored healthcare, AI enhances user experiences by addressing individual needs.

Increased Safety: In sectors like automotive and manufacturing, AI-driven systems contribute to improved safety and accident prevention.

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7. Disadvantages and Challenges

Despite its many benefits, AI also presents several challenges:

Job Displacement: Automation and AI can lead to job losses in certain sectors, raising concerns about workforce displacement.

Bias and Fairness: AI systems can perpetuate biases present in training data, leading to unfair outcomes in areas like hiring or law enforcement.

Privacy Issues: The use of large datasets often involves sensitive personal information, raising concerns about data privacy and security.

Complexity and Cost: Developing and maintaining AI systems requires significant resources, expertise, and financial investment.

Ethical Concerns: The increasing autonomy of AI systems brings ethical dilemmas, such as accountability for decisions made by machines.

Source: Nature – The Ethics of AI

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8. Tips for Embracing AI Responsibly

For individuals and organizations looking to harness the power of AI, consider these practical tips:

Invest in Education and Training: Upskill your workforce by offering training in AI and data science to stay competitive.

Prioritize Transparency: Ensure that AI systems are transparent in their operations, especially when making decisions that affect individuals.

Implement Robust Data Security Measures: Protect user data with advanced security protocols to prevent breaches and misuse.

Monitor and Mitigate Bias: Regularly audit AI systems for biases and take corrective measures to ensure fair outcomes.

Stay Informed on Regulatory Changes: Keep abreast of evolving legal and ethical standards surrounding AI to maintain compliance and public trust.

Foster Collaboration: Work with cross-disciplinary teams, including ethicists, data scientists, and industry experts, to create well-rounded AI solutions.

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9. Future Outlook

The future of AI is both promising and challenging. With continuous advancements in technology, AI is expected to become even more integrated into our daily lives. Innovations such as AGI and even discussions around ASI signal potential breakthroughs that could revolutionize every sector—from education and healthcare to transportation and beyond. However, these advancements must be managed responsibly, balancing innovation with ethical considerations to ensure that AI benefits society as a whole.

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10. Conclusion

Artificial Intelligence is a dynamic field that continues to evolve, offering incredible opportunities while posing significant challenges. By understanding the various types of AI, its real-world applications, and the associated advantages and disadvantages, we can better prepare for an AI-driven future. Whether you are a business leader, a policymaker, or an enthusiast, staying informed and adopting responsible practices will be key to leveraging AI’s full potential.

As we move forward, it is crucial to strike a balance between technological innovation and ethical responsibility. With proper planning, education, and collaboration, AI can be a force for good, driving progress and improving lives around the globe.

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References

1. MIT Technology Review – https://www.technologyreview.com/

2. Stanford University AI Index – https://aiindex.stanford.edu/

3. Forbes – https://www.forbes.com/

4. Nature – https://www.nature.com/

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Explore our comprehensive 1,000-word guide on Artificial Intelligence, covering its history, types, real-world applications, advantages, disadvantages, and practical tips for responsible adoption. Learn how AI is shaping the future while addressing ethical and operational challenges.

[ptitolier]

Progress can be a ladder or a cage.

Verne vs. Orwell: Is Progress Leading Us to Utopia or Dystopia?

Since the dawn of time, humanity has asked: Is progress a blessing or a curse?

Jules Verne imagined a future where technology empowers and emancipates.

George Orwell warned us that progress could become a prison.

Two visions of the future that seem opposed, yet they may be more connected than we think.

Today, we live in a world where Verne’s dreams and Orwell’s fears coexist:

Technological advancements open incredible possibilities.

But they also threaten our fundamental freedoms.

Are we building Verne’s utopia or Orwell’s dystopia?

"Technological progress without conscience is nothing but the ruin of the soul." – Rabelais

Jules Verne and the Promise of Progress

Verne was a visionary, deeply influenced by the scientific boom of the 19th century.

An Era of Technological Optimism

Industrialization was transforming the world.

Travel was becoming more accessible.

Innovation was seen as a tool for social progress.

Verne believed in progress as a way to push the boundaries of humanity.

Predictions That Became Reality

From the Earth to the Moon → Space travel and Mars missions.

20,000 Leagues Under the Sea → Deep-sea exploration and underwater robotics.

The Mysterious Island → Renewable energy and self-sufficiency.

Verne reminds us that technology is a powerful tool—if used for the common good.

💬 "Science has made us gods before we even deserved to be men." – Jean Rostand

Yet, Verne was not naive. He foresaw the dangers of misused progress, as seen in Captain Nemo, who isolates himself and seeks revenge using technology.

Are we heading toward enlightened progress—or a dangerous drift?

Orwell and the Fear of Totalitarian Progress

George Orwell wrote in a very different context—the 20th century, marked by world wars and rising totalitarian regimes.

His warning: Every technology can become a tool of control.

Prophecies That Came True

1984 warns of a world where information is manipulated, every action is monitored, and even thought is controlled.

Some of these fears have become reality today:

Big Brother and mass surveillance → Smart cameras, facial recognition, digital tracking.

Newspeak and rewriting history → Fake news, algorithmic manipulation of facts.

The Ministry of Truth and public opinion control → Social media shaping beliefs and behaviors.

Orwell warned us: Progress can also be an instrument of domination.

💬 "Who controls the past controls the future. Who controls the present controls the past." – Orwell

The Modern Paradox: Utopia and Dystopia at the Same Time

Where do we stand between Verne and Orwell?

We are witnessing a fascinating paradox:

The innovations that could save us are also the ones that could enslave us.

Concrete Examples:

AI helps us solve problems… but also manipulates information and influences decisions.

Space exploration is a remarkable achievement… but is it an escape from our responsibilities on Earth?

Biotechnology and transhumanism can improve human life… but could they increase inequality?

"History is a loop we must learn to break." – Nietzsche

A Philosophical Question: Where Do We Set the Limits?

The philosopher Hans Jonas, in The Imperative of Responsibility, reminds us:

"The more our technological power grows, the greater our responsibility becomes."

Do we have the safeguards needed to regulate these transformations?

Should AI be controlled to prevent abuse?

Is space exploration a real solution or just a fantasy?

How do we prevent scientific advancements from becoming tools of oppression?

We have the means to create a utopia—but do we have the wisdom to avoid a dystopia?

What Future Do We Want?

We live in a world where Verne’s visions and Orwell’s warnings coexist:

We have innovations worthy of Verne’s imagination.

We face the dangers Orwell predicted.

The future depends on our ability to guide progress responsibly.

Are we choosing between Verne’s utopia and Orwell’s dystopia—or must we invent a new model?

I explore this dilemma in depth in my latest article on Medium:

And you—do you see the future more like Verne or Orwell?

P'tit Tôlier

Essayist & Popularizer. I analyze the world through accessible philosophical essays. Complex ideas, explained simply—to help us think about our times.

[mozarting]

Day 4: Traits in Rust & Sets and Sorting in Algorithms

Today, I studied Traits in Rust. At first, from the first Rust Book example it wasn't clear to me that why I need trait to implement this. As I went on, the concept started to make more sense, but things got complicated like with trait bounds syntax and the where clause. Honestly, I don’t think it’ll fully click until I have to use them in an actual project.

Algorithms: Lecture 3 – Sets and Sorting

On the algorithms side, I watched Lecture 3, which covered sets and sorting. Algorithms were quite clear, the lecturer was energetic, It’s still pretty math-heavy, and some of it went over my head. Since I’m more interested in learning how to implement algorithms than getting deep into the math, I’ll probably bring in other resources to supplement what I’m learning here.

Tomorrow's plan

When I committed to working daily on Rust, learning algorithms, and posting on Tumblr, I set up a timetable and stuck to it for the first two days. My motivation was high, and I felt productive. But since yesterday, I’ve started slipping, and I can feel my productivity fading—which I don’t want to let happen.

My goal now is to push myself to stay disciplined until this becomes a habit. Tomorrow, I’ll keep going with the Rust Book and tackle the final topic of this chapter: Validating References with Lifetimes..

[thursdayisbetterthanfriday]

Atom: The Beginning & AI Cybersecurity

Atom: The Beginning is a manga about two researchers creating advanced robotic AI systems, such as unit A106. Their breakthrough is the Bewusstein (Translation: awareness) system, which aims to give robots a "heart", or a kind of empathy. In volume 2, A106, or Atom, manages to "beat" the highly advanced robot Mars in a fight using a highly abstracted machine language over WiFi to persuade it to stop.

This may be fiction, but it has parallels with current AI development in the use of specific commands to over-run safety guides. This has been demonstrated in GPT models, such as ChatGPT, where users are able to subvert models to get them to output "banned" information by "pretending" to be another AI system, or other means.

There are parallels to Atom, in a sense with users effectively "persuading" the system to empathise. In reality, this is the consequence of training Large Language Models (LLM's) on relatively un-sorted input data. Until recent guardrail placed by OpenAI there were no commands to "stop" the AI from pretending to be an AI from being a human who COULD perform these actions.

As one research paper put it:

"Such attacks can result in erroneous outputs, model-generated hate speech, and the exposure of users’ sensitive information." Branch, et al. 2022

There are, however, more deliberately malicious actions which AI developers can take to introduce backdoors.

In Atom, Volume 4, Atom faces off against Ivan - a Russian military robot. Ivan, however, has been programmed with data collected from the fight between Mars and Atom.

What the human researchers in the manga didn't realise, was the code transmissions were a kind of highly abstracted machine level conversation. Regardless, the "anti-viral" commands were implemented into Ivan and, as a result, Ivan parrots the words Atom used back to it, causing Atom to deliberately hold back.

In AI cybersecurity terms, this is effectively an AI-on-AI prompt injection attack. Attempting to use the words of the AI against itself to perform malicious acts. Not only can this occur, but AI creators can plant "backdoor commands" into AI systems on creation, where a specific set of inputs can activate functionality hidden to regular users.

This is a key security issue for any company training AI systems, and has led many to reconsider outsourcing AI training of potential high-risk AI systems. Researchers, such as Shafi Goldwasser at UC Berkley are at the cutting edge of this research, doing work compared to the key encryption standards and algorithms research of the 1950s and 60s which have led to today's modern world of highly secure online transactions and messaging services.

From returning database entries, to controlling applied hardware, it is key that these dangers are fully understood on a deep mathematical, logical, basis or else we face the dangerous prospect of future AI systems which can be turned against users.

As AI further develops as a field, these kinds of attacks will need to be prevented, or mitigated against, to ensure the safety of systems that people interact with.

References:

Twitter pranksters derail GPT-3 bot with newly discovered “prompt injection” hack - Ars Technica (16/09/2023)

EVALUATING THE SUSCEPTIBILITY OF PRE-TRAINED LANGUAGE MODELS VIA HANDCRAFTED ADVERSARIAL EXAMPLES - Hezekiah Branch et. al, 2022 Funded by Preamble

In Neural Networks, Unbreakable Locks Can Hide Invisible Doors - Quanta Magazine (02/03/2023)

Planting Undetectable Backdoors in Machine Learning Models - Shafi Goldwasser et.al, UC Berkeley, 2022