Pioneering musical concept Anyma links with multi-talented artist Chris Avantgarde to create “Consciousness.” The single’s euphoric arpeggios, sleek synths, and futuristic vocals complement the infinite aesthetic of Anyma’s mind-bending NFT.

“Consciousness” was set finally released with Afterlife Recordings on May 18th after months of playtime by the Afterlife lineup. The single will also be tokenized as an NFT via Anyma’s newly formed DAOxfit (Decentralized Autonomous Organization), known as EVA DAO.

The innovative collaboration by the two ambitious artists will undeniably be remembered as one of 2022’s most captivating productions. The NFT is described on its website as “the sentience of internal, external, or virtual existence”.

Anyma explains how he and Chris created “Consciousness” through their musical interpolation to connect the real and virtual world. It is further explained that this sonic bridge created between web3 and web2 is connected the future and the past of music and visual art. Using web 3, EVA DAO evolves the fan experience to be immersive, intimate, and impactful.

Matteo Milleri, also known as Anyma, is utilizing the infinite possibilities of extended reality by creating an interactive space that will encourage artists’ ownership in their creative human expression. EVA DAO will focus on exploring live visual experiences while aiming to improve the way artists independently finance and share their vision.

EVA DAO’s first showcase will be presented in the form of an NFT. The highly curated collection will be showcased at the prestigious Palazzo Strozzi in Florence, Italy for the Let’s Get Digital! exhibition. Anyma has also previously teased the ID at memorable live performances such as Afterlife in Sao Paulo, Brasil, and Ultra Music Festival in Miami, Florida.

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Ever wonder how many petals are on an Artichoke? Or more importantly wonder how a learning group might approach this situation? It proves to be a great way to get learning groups to think about the scientific process, make and test predictions, and study the resulting data.

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A research team trained the algorithm by having it go through data collected by NASA’s now-retired Kepler Space Telescope, which spent nine years in deep space on a world-hunting mission. Once the algorithm learned to accurately separate real planets from false positives, it was used to analyze old data sets that had not yet been confirmed — which is where it found the 50 exoplanets.

These 50 exoplanets, which orbit around other stars, range in size from as large as Neptune to smaller than Earth, the university said in a news release. Some of their orbits are as long as 200 days, and some as short as a single day. And now that astronomers know the planets are real, they can prioritize them for further observation.

The algorithm could “validate thousands of unseen candidates in seconds,” the study indicated. And because it’s based on machine learning, it can still be improved upon, and can continue to become more effective with each new discovery.

Join in and build bright sentience on the island of Evolve. Leapfrog your career, your life, and the world.

In each city, you can go to the university to learn both fundamental and groundbreaking tools about given technology or open-source field.

You can also go play missions either single player or visit dungeons and temples in raids of five and thirty players respectively, where you level up by developing the existing opens source infrastructure of the city.

Create or elaborate on their common Altrupedia. From here you can design cities on the island by co-creating roadmaps and increase their abundance. Go to their wiki and sign up, edit pages, and create the solutions on Optimal Altruism with teams all over the world who share your passion.

Technology Tree towards Pandoraforming Earth and Beyond

To learn more about Optimal Altruism visit https://www.optimalaltruism.com/about-evolve/ or https://www.optimalaltruism.com/

It’s the year 2055 and what once was a toy rabbit awkwardly hopping on its own mechanical whim, is now jumping and running faster than a human. It can now, with fluid motion, jump over a large truck and continue its smooth stride. It’s not human enough to try out for the Olympics, however it has been recognized as the fastest techno-rabbit on the block and receives an award from the Guinness Book of A.I. achievements for furthest mecha-leaper. Chanting and cheers erupt from the audience as other animal mechanoids yield support for their ‘tricks aren’t for kids’ futuristic friend.

With advances in AGI (Artificial General Intelligence) climaxing and with the potential future singularity, how can we leverage the power of singularity with imperfect humanism. It may be that, we need to create a sense of forced fallibility within superintelligent systems by means of machine learning clauses, vital awareness, and ethical statutes.

For humans, our obvious vital source of energy comes from food, and conversely for most robots it’s electricity. We display different varying levels of energy and moods dependent upon what types foods and amounts we eat. Similarly with future superintelligent machines, electrical power adjustments and machine learning algorithmic clauses could determine a mood for a robot by increasing or decreasing throughput and processing speed in relation to their specific power levels. The hibernation of a system depleted of electricity and energy constraints could be analogous to a human nap.

Quantum battery discoveries show us the possibility of near perpetual energy, however perhaps this is the ultimate downside and scare towards integrating superintelligence fashioned by a bot. By utilizing neural networks containing vitals data, most importantly variable electricity levels, a superintelligent robot could be aware of its own varying power supply and increase or decrease its activities accordingly to its fixed energy capacity, and perhaps even its own throughput.

A.I. ethical commandments from an oversight committee could help humanity if the singularity ever occurs. By utilizing brute force fallibility measures into an A.I. systems, such that it learns and trains in accordance to our own imperfection sense, then maybe we can keep A.I. levels at somewhat of a stand still, with it not exponentially increasing above the calculations and throughput of the human brain.

Philosophers have wondered whether it is possible for one to ever be certain, at any given point in time, that one is not in fact dreaming, and never experience reality of wakefulness at all. Our senses allow us to perceive our environment, but is our environment part of objective reality?

Quantum fluctuations and multiverse theory suggest the possibility of multiple iterations of “you” performing different objectives at the same time. While you drove to work this morning, another version of you went to the park and took a walk. The objective reality that we experience is only a fraction of an infinite amount of possible outcomes.

Consider a raindrop and its propagating waves after a collision. Imagine the raindrop is your observable conscious system, and that each wave that it creates is an iteration of your reality. Perhaps during our REM sleep stage, which allows us some of the most intense dreaming, your current dream state isn’t a fabrication of the mind, but an observation of an alternate iteration of you in another place in space and time. Perhaps this dream state awareness or pseudo-simulation of ourselves is actually a training neural network type system that allows us to function more efficiently in our waking state.

Could datasets from dream blogging or dream recollection allow a predictive model of a more efficient self? The correlation between dreams and waking life focus could introduce a new era of self improvement and give credence and pathways to self-conscious AI.

Motor intelligence involves learning how to maneuver and coordinate a flexible body to solve tasks in a range of complex environments. Such attempts to control physically simulated humanoid bodies come from diverse fields, including computer animation and biomechanics. Recent trends involve hand-crafted objectives, sometimes with motion capture data, and to produce specific behaviors. However, this may require considerable engineering effort, and can result in restricted behaviors or behaviors that may be difficult to repurpose for new tasks.

Google’s Deepmind project exhibits how sophisticated behaviors can emerge from the body interacting with the environment using only simple high-level objectives, such as moving forward without falling. Specifically, Google has trained agents with a variety of simulated bodies to make progress across diverse terrains, which require jumping, turning and crouching. The results show the agents develop these complex skills without receiving specific instructions, an approach that can be applied to train their systems for multiple, distinct simulated bodies.

It’s a sultry 90 degrees outside and you’ve discovered your coffee is still warm after sitting 2 hours. To pass some time you decide to check some email on your laptop and browse some of your favorite websites. After your most recent gander of web advertisement glorification you notice something somewhat familiar with the last several websites you visited. The verdict is conclusive and you start to ponder: “Wow, I love the large cover image/video with scrolling hover elements, but could there be something more creative or different to capture my users attention?”. Web 2.0 has come and passed, what’s next when it comes to App development and responsive web?.

Some of our top leading development strategists and innovators including Elon Musk of SpaceX suggest that a lack of innovation will eventually lead to stagnation. Creativity and ingenuity are lead characteristics of humanity that closely follow suit with innovation and so we expect increasing evolutionary phases of transformation as the time pendulum swings.

So what’s the next phase of web development? Web 3.0, or the ‘intelligent web‘ could include semantic web, microformats, natural language search, Metaverse, data-mining, machine learning, recommendation agents, and artificial intelligence technologies.

It’s been stated that object oriented programming creates living, breathing, entities that have knowledge inside them and can remember things. While this archaic idea by Steve Jobs still has some validity today, how does this relate to the future of emerging trends such as machine learning, quantum computing, neural networks, and Artificial Intelligence? Will Web 3.0 standardize deep A.I. and machine learning to bring about a post-modern self-conscious web where communication is transmissible via our thoughts or dreams?

According to Susan Schneider, and in her recent book, Artificial You: AI and the Future of the Mind, she discusses a philosophical exploration of what A.I. can and cannot achieve. She also discusses the pros and cons of what mind design enhancements may look like with the potential of future machine-mind hybrids.

How do you see Web 3.0 changing and evolving? Contact us and let us know.

With strife and hardship among our populous brought forth from epidemics such as COVID-19 and other impeding diseases of the future, it’s imperative that web-based alert response systems handle the appropriate measures to sustain the load of their forthcoming citizens who are in need of help. Load balancing servers and indexing databases properly are just a few tricks of trade to handle massive amounts of concurrent users during a panic of online necessity. Proper integration of these services can make the difference in saving families and individuals in attentive need of support.

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