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A cornerstone of the technology that is shifting the way we go about our lives is artificial intelligence (AI). Also known as machine intelligence or machine learning, AI is the development of computer-driven technology used to perform functions and tasks that previously required human intelligence. That said, AI ETFs are reaping the benefits.

Within the sprawling AI universe, there are four pillars: reactive machines, limited memory, theory of mind and self-awareness. An example of reactive machines would be the famous Deep Blue chess-playing supercomputer from IBM (NYSE:IBM) while autonomous and self-driving vehicles would be examples of technologies in the limited memory category.

Everyday applications of AI include Apples (NASDAQ:AAPL) SIRI, Alphabet (NASDAQ:GOOG, NASDAQ:GOOGL) search algorithim and Amazons (NASDAQ:AMZN) Alexa.

Those are basic forms of AI, but they serve as evidence of the markets growth and utility. Investors can harness those trends and more by taking advantage of the opportunities in AI ETFs.

That said, lets take a look at a few.

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Expense Ratio: 0.75% per year, or $75 on a $10,000 investment

For investors looking for disruptive technology exposure, the actively managed ARK Innovation ETF (NYSEARCA:ARKK) fits the bill. The fund has a wide reach that encompasses not just pure AI, but industries using this next generation technology.

ARKK companies run the gamut of genomic firms, fintech providers, next generation internet (shared work and related infrastructure) and industrial innovation, among others. Like some other ARK funds, ARKK is know for its large weight to Tesla (NASDAQ:TSLA), which is more than 10%. However, it features plenty of other high fliers with dominant positioning in their respective markets, including Square (NYSE:SQ) and Illumina (NASDAQ:ILMN).

Moreover, some of ARKKs allure as an AI ETF is realized through its exposure to the deep-learning market a truly compelling long-term trend.

In fact, ARK believes that deep learning will be more impactful than the Internet:

The Internet created roughly $10 trillion in global equity market capitalization in 20 years. We believe that deep learning will have 3x that impact, adding $30 trillion to global equity markets over the next two decades.

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Expense Ratio: 0.68% per year

The Global X Robotics & Artificial Intelligence ETF (NASDAQ:BOTZ) is an established giant in the world of AI ETFs with over $1 billion in assets under management and a track record spanning nearly four years.

The fund holds 38 stocks and its top holding is Nvidia (NASDAQ:NVDA), a name with deep AI credibility. That stock accounts for the bulk of the semiconductor exposure in BOTZ. Underscoring this funds diversity, BOTZ features allocations to 14 industry groups, including chip makers.

Importantly, BOTZ provides exposure to increasing efficiencies in the AI universe. In turn, these are widely viewed as a vital long-term driver of AI investment outcomes.

In the past, training robotics was laborious and required time, capital, and engineering expertise, but AI simulators are becoming increasingly accurate at transferring learning to real world applications, according to Global X research. These simulators can run thousands of iterative processes in seconds, creating vast amounts of training data.

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Expense Ratio: 0.40%

The Defiance Quantum ETF (NYSEARCA:QTUM) is one of the premier AI ETFs when it comes to accessing the deep and machine learning themes. The funds underlying benchmark the BlueStar Quantum Computing and Machine Learning Index provides robust exposure to those markets.

Home to 60 stocks, QTUMs index gives the fund a deeper bench than many competing AI ETFs. QTUM itself has 84 holdings.

QTUM components are involved in quantum computing, which data indicates QTUMs exposure to this burgeoning theme could be a positive long-term driver.

The global commercial quantum computing market is expected to reach $1.3 billion by 2027 at a compound annual growth rate (CAGR) of 52.9% from 2022 to 2027 and $161 million by 2022 from $33.0 million in 2017 at a CAGR of 37.3% for the period 2017-2022, notes BCC Research.

Todd Shriber has been an InvestorPlace contributor since 2014. As of this writing, he did not hold a position in any of the aforementioned securities.

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3 AI ETFs Changing The World - Investorplace.com

The race to build the best and the fastest quantum computer continues, but now it's not just Google AI and IBM who are running Honeywell has joined in too.

Entering in style, Honeywell made the bold statement that "By the middle of 2020, we're releasing the most powerful quantum computer yet."

SEE ALSO: IBM'S 53 QUBIT QUANTUM COMPUTER WILL BE AVAILABLE BY OCTOBER

Google AI and IBM have been in the race for a while now. Just last October Google claimed to have made it to "quantum supremacy" by creating a quantum computer that could solve a problem that would have taken the world's most powerful supercomputer 10,000 years to figure out.

Immediately after, IBM refuted Google's statement.

Perhaps it's now time for both Google and IBM to move aside and let a third contender join in on the fun. North Carolina-based multinational conglomerate, Honeywell, has claimed that their quantum computer has twice the power as the best quantum computer that currently exists.

It's an interesting statement to make given there isn't yet a universally accepted standard for the power of a quantum computer.

Honeywell's quantum computer is supposedly extremely stable, and instead of depending on faster superconducting chips like Google AI and IBM use, Honeywell's computer uses ion traps instead. This technology enables individual ions to be held in place using electromagnetic fields and moves around thanks to laser pulses.

It's these ion traps that Honeywell claims will make its quantum computer far more scaleable.

We're yet to see a commercially available quantum computer, however, these technologies hold the real potential to revolutionize computing by being able to solve unbelievably long and complicated numerical problems simultaneously by using qubits instead of bits.

After Honeywell's rather large claim, the company has yet to reveal the computer but as they stated, we'll just have to wait until the middle of 2020.

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Honeywell Claims to Have Built the "Most Powerful" Quantum Computer - Interesting Engineering

Inside the race to build the best quantum computer on Earth - ET Prime

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Why IBM thinks quantum supremacy is not the milestone we should care about.

Neerja Sundaresan, research team member of IBM Research, talks to her colleague Douglas McClure, next to an IBM Q System One quantum computer at IBM's research facility in New York.

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Competitors are monitoring the Toyota-Suzuki integration and are hoping for a slowdown in decision making. But a sluggish Indian market isnt attractive enough for them to put in money and effort to snatch Marutis market share. Indias largest carmaker, however, faces profitability hurdles, among other challenges. Last of a two-part series.

Startups such as WorkIndia, Betterplace, Awign, and Utter have ushered in the digital age for blue-collar job search. Today, millions of such workers are using the apps of these companies to find jobs, pick up skills, and run gigs. However, the segment largely remains a niche for impact investors, with mainstream VCs still watching from the sidelines.

RBIs proposed write-down of Yes Banks perpetual bonds has grave implications for Indias ailing financial system. The country cant be seen as indifferent to creditor obligations. It couldnt have come at a worse time just when India is making efforts to quickly expand its small bond market and tap international debt markets through a larger presence in global bond indices.

The deadly coronavirus has taken a toll on the global economy, with the Indian stock market also becoming a casualty. While the NSEs benchmark index, Nifty, is down by 7% over the last one month, the Quality Index has largely held steady. And investors, who paid high valuations for these stocks, are relatively unhurt.

Though zero-alcohol beer has grown immensely popular in the country within a short span, cola giants dismiss the segment as too tiny to worry about. But attractive pricing and rapidly shifting consumer preferences give the beer zero category a clear edge. Hence, industry participants believe it can create a dent in the market share of cola giants.

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Inside the race to build the best quantum computer on Earth - Economic Times

UC Riverside (UCR) is set to lead a project focused on enabling scalable quantum computing after winning a $3.75 million Multicampus-National Lab Collaborative Research and Training Award.

The collaborative effort will see contributions from UC Berkeley, UCLA and UC Santa Barbara, with UCR acting as project coordinator.

Scalable quantum computing

Quantum computing is currently in its infancy but it is expected to stretch far beyond the capabilities of conventional computing in the coming years. Intensive tasks such as modeling complex processes, finding large prime numbers, and designing new chemical compounds for medical use are what quantum computers are expected to excel at.

Quantum information is stored on quantum computers in the form of quantum bits, or qubits. This means that quantum systems can exist in two different states simultaneously as opposed to conventional computing systems which only exist in one state at a time. Current quantum computers are limited in their qubits, however, so for quantum computing to realize its true potential, new systems are going to have to be scalable and include many more qubits.

The goal of this collaborative project is to establish a novel platform for quantum computing that is truly scalable up to many qubits, said Boerge Hemmerling, an assistant professor of physics and astronomy at UC Riverside and the lead principal investigator of the three-year project. Current quantum computing technology is far away from experimentally controlling the large number of qubits required for fault-tolerant computing. This stands in large contrast to what has been achieved in conventional computer chips in classical computing.

3D printed ion trap microstructures

The research team will use advanced 3D printing technology, available at Lawrence Livermore National Laboratory, to fabricate microstructure ion traps for the new quantum computers. Ions are used to store qubits and quantum information is transferred when these ions move in their traps. According to UCR, trapped ions have the best potential for realizing scalable quantum computing.

Alongside UCR, UC Berkeley will enable high-fidelity quantum gates with the ion traps. UCLA will integrate fiber optics with the ion traps, UC Santa Barbara will put the traps through trials in cryogenic environments and demonstrate shuttling of ion strings while the Lawrence Berkeley National Laboratory will be used to characterize and develop new materials. The project coordinator, UCR, will develop simplified cooling schemes and research the possibility of trapping electrons with the traps.

We have a unique opportunity here to join various groups within the UC system and combine their expertise to make something bigger than a single group could achieve, Hemmerling stated. We anticipate that the microstructure 3D printed ion traps will outperform ion traps that have been used to date in terms of the storage time of the ions and ability to maintain and manipulate quantum information.

He adds, Most importantly, our envisioned structures will be scalable in that we plan to build arrays of interconnected traps, similar to the very successful conventional computer chip design. We hope to establish these novel 3D-printed traps as a standard laboratory tool for quantum computing with major improvements over currently used technology.

Hemmerlings concluding remarks explain that many quantum computing approaches, while very promising, have fallen short of providing a scalable platform that is useful for processing complex tasks. If an applicable machine is to be built, new routes must be considered, starting with UCRs scalable computing project.

Early quantum technology work involving 3D printing has paved the way for UCRs future project. When cooled to near 0K, the quantum characteristics of atomic particles start to become apparent. Just last year, additive manufacturing R&D company Added Scientific 3D printed the first vacuum chamber capable of trapping clouds of cold atoms. Elsewhere, two-photon AM system manufacturer Nanoscribe introduced a new machine, the Quantum X, with micro-optic capabilities. The company expects its system to be useful in advancing quantum technology to the industrial level.

The nominations for the 2020 3D Printing Industry Awards are now open. Who do you think should make the shortlists for this years show? Have your say now.

Subscribe to the 3D Printing Industry newsletter for the latest news in additive manufacturing. You can also stay connected by following us on Twitter and liking us on Facebook.

Looking for a career in additive manufacturing? Visit 3D Printing Jobs for a selection of roles in the industry.

Featured image showsUniversity of California, Riverside campus. Photo via UCR.

Link:
UC Riverside to lead scalable quantum computing project using 3D printed ion traps - 3D Printing Industry

AI is one of the most happening domains in the world right now. It would take a lifetime to skim through all the machine learning research papers released till date. As the AI keeps itself in the news through new releases of frameworks, regulations and breakthroughs, we can only hope to get the best of the lot.

So, here we have a compiled a list of top exciting AI announcements released over the past one week:

Late last year, Google locked horns with IBM in their race for quantum supremacy. Though the news has been around how good their quantum computers are, not much has been said about the implementation. Today, Google brings two of their most powerful frameworks Tensorflow and CIRQ together and releases TensorFlow Quantum, an open-source library for the rapid prototyping of quantum ML models.

Google AI team has joined hands with the University of Waterloo, X, and Volkswagen, announced the release of TensorFlow Quantum (TFQ).

TFQ is designed to provide the developers with the tools necessary for assisting the quantum computing and machine learning research communities to control and model quantum systems.

The team at Google have also released a TFQ white paper with a review of quantum applications. And, each example can be run in-browser via Colab from this research repository.

A key feature of TensorFlow Quantum is the ability to simultaneously train and execute many quantum circuits. This is achieved by TensorFlows ability to parallelise computation across a cluster of computers, and the ability to simulate relatively large quantum circuits on multi-core computers.

As the devastating news of COVID-19 keeps rising at an alarming rate, the AI researchers have given something to smile about. DeepMind, one of the premier AI research labs in the world, announced last week, that they are releasing structure predictions of several proteins that can promote research into the ongoing research around COVID-19. They have used the latest version of AlphaFold system to find these structures. AlphaFold is one of the biggest innovations to have come from the labs of DeepMind, and after a couple of years, it is exhilarating to see its application in something very critical.

As the pursuit to achieve human-level intelligence in machines fortifies, language modeling will keep on surfacing till the very end. One, human language is innately sophisticated, and two, training language models from scratch is exhaustive.

The last couple of years has witnessed a flurry of mega releases from the likes of NVIDIA, Microsoft and especially Google. As BERT topped the charts through many of its variants, Google now announces ELECTRA.

ELECTRA has the benefits of BERT but more efficient learning. They also claim that this novel pre-training method outperforms existing techniques given the same compute budget.

The gains are particularly strong for small models; for example, a model trained on one GPU for four days outperformed GPT (trained using 30x more compute) on the GLUE natural language understanding benchmark.

China has been the worst-hit nation of all the COVID-19 victims. However, two of the biggest AI breakthroughs have come from the Chinese soil. Last month, Baidu announced how its toolkit brings down the prediction time. Last week, another Chinese giant, Alibaba announced that its new AI system has an accuracy of 96% in detecting the coronavirus from the CT scan of the patients. Alibabas founder Jack Ma has fueled the vaccine development efforts of his team with a $2.15 M donation.

Facebook AI has released its in-house feature of converting a two-dimensional photo into a video byte that gives the feel of having a more realistic view of the object in the picture. This system infers the 3D structure of any image, whether it is a new shot just taken on an Android or iOS device with a standard single camera, or a decades-old image recently uploaded to a phone or laptop.

The feature has been only available on high-end phones through the dual-lens portrait mode. But, now it will be available on every mobile device even with a single, rear-facing camera. To bring this new visual format to more people, the researchers at Facebook used state-of-the-art ML techniques to produce 3D photos from virtually any standard 2D picture.

One significant implication of this feature can be an improved understanding of 3D scenes that can help robots navigate and interact with the physical world.

As the whole world focused on the race to quantum supremacy between Google and IBM, Honeywell silently has been building, as it claims, the most powerful quantum computer yet. And, it plans to release this by the middle of 2020.

Thanks to a breakthrough in technology, were on track to release a quantum computer with a quantum volume of at least 64, twice that of the next alternative in the industry. There are a number of industries that will be profoundly impacted by the advancement and ultimate application of at-scale quantum computing, said Tony Uttley, President of Honeywell Quantum Solutions in the official press release.

The outbreak of COVID-19 has created a panic globally and rightfully so. Many flagship conferences have been either cancelled or have been moved to a virtual environment.

Nvidias flagship GPU Technology Conference (GTC), which was supposed to take place in San Francisco in the last week of March was cancelled due to fears of the COVID-19 coronavirus.

Whereas, Google Cloud also has cancelled its upcoming event, Google Cloud Next 20, which was slated to take place on April 6-8 at the Moscone Center in San Francisco. Due to the growing concern around the coronavirus (COVID-19), and in alignment with the best practices laid out by the CDC, WHO and other relevant entities, Google Cloud has decided to reimagine Google Cloud Next 20, the company stated on its website.

One of the popular conferences for ML researchers, ICLR2020 too, has announced that they are cancelling its physical conference this year due to growing concerns about COVID-19. They are shifting this event to a fully virtual conference.

ICLR authorities also issued a statement saying that all accepted papers at the virtual conference will be presented using a pre-recorded video.

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Top AI Announcements Of The Week: TensorFlow Quantum And More - Analytics India Magazine