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On May 13th, Terence Tao, an award winning Australia-born Chinese mathematician, announced that he and physicist Laura Greene will co-chair a working group studying the impacts of generative artificial intelligence technology on the Presidential Council of Advisors on Science and Technology (PCAST). The group will hold a public meeting during the PCAST conference on May 19th, where Demis Hassabis, founder of DeepMind and creator of AlphaGo, as well as Stanford University professor Fei-Fei Li among others will give speeches.

According to Terence Taos blog, the group mainly researches the impact of generative AI technology in scientific and social fields, including large-scale language models based on text such as ChatGPT, image generators like DALL-E 2 and Midjourney, as well as scientific application models for protein design or weather forecasting. It is worth mentioning that Lisa Su, CEO of AMD, and Phil Venables, Chief Information Security Officer of Google Cloud are also members of this working group.

According to an article posted on the official website of the White House, PCAST develops evidence-based recommendations for the President on matters involving science, technology, and innovation policy, as well as on matters involving scientific and technological information that is needed to inform policy affecting the economy, worker empowerment, education, energy, the environment, public health, national and homeland security, racial equity, and other topics.

SEE ALSO: Mathematician Terence Tao Comments on ChatGPT

After the emergence of ChatGPT, top mathematicians like Terence Tao also paid great attention to it and began exploring how artificial intelligence could help them complete their work. In an article titled How will AI change mathematics? Rise of chatbots highlights discussion in the Nature Journal, Andrew Granville, a number theorist at McGill University in Canada, also said that we are studying a very specific question: will machines change mathematics? Mathematician Kevin Buzzard agrees, saying that in fact, now even Fields Medal winners and other very famous mathematicians are interested in this field, which shows that it has become popular in an unprecedented way.

Previously, Terence Tao wrote on the decentralized social network Mastodon, Today was the first day that I could definitively say that #GPT4 has saved me a significant amount of tedious work. In his experimentation, Terence Tao discovered many hidden features of ChatGPT such as searching for formulas, parsing documents with code formatting, rewriting sentences in academic papers and sometimes even semantically searching incomplete math problems to generate hints.

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Terence Tao Leads White House's Generative AI Working Group ... - Pandaily

By Gaurav Yadav, Second year, Law

In 1955, four scientists coined the term artificial intelligence (AI) and embarked on a summer research project aimed at developing machines capable of using language, forming abstractions and solving problems typically reserved for humans. Their ultimate goal was to create machines rivalling human intelligence. The past decade has witnessed a remarkable transformation in AI capabilities, but this rapid progress should prompt more caution than enthusiasm.

The foundation of AI lies in machine learning, a process by which machines learn from data without explicit programming. Using vast datasets and statistical methods, algorithms identify patterns and relationships in the data, later using these patterns to make predictions or decisions on previously unseen data. The current paradigm in machine learning involves developing artificial neural networks that mimic the human brain's structure.

AI systems can be divided into two categories: 'narrow' and 'general'. A 'narrow' AI system excels in specific tasks, such as image recognition or strategic games like chess or Go, whereas artificial general intelligence (AGI) refers to a system proficient across a wide range of tasks, comparable to a human being.

A growing number of people worry that the emergence of advanced AI could lead to an existential crisis. Advanced AI broadly means AI systems capable of performing all cognitive tasks typically completed by humansenvision an AI system managing a company's operations as its CEO.

Daniel Eth, a former research scholar at the Future of Humanity Institute, University of Oxford, describes the potential outcome for advanced AI as one that could involve a single AGI surpassing human experts in most fields and disciplines. Another possibility entails an ecosystem of specialised AI systems, collectively capable of virtually all cognitive tasks. While researchers may disagree on the necessity of AGI or whether current AI models are approaching advanced capabilities, a general consensus exists that advanced or transformative AI systems are theoretically feasible.

Though certain aspects of this discussion might evoke a science fiction feel, recent AI breakthroughs seem to have blurred the line between fantasy and reality. Notable examples include large language models like GPT-4 and AlphaGo's landmark victory over Lee Sedol. These advancements underscore the potential for transformative AI systems in the future. AI systems can now recognise images, produce videos, excel at StarCraft, and produce text that is indistinguishable from human writing. The state of the art in AI is now a moving target, with AI capabilities advancing year after year.

Why should we be concerned about advanced AI?

If advanced AI is unaligned with human goals, it could pose significant risks for humanity. The 'alignment problem'which is the problem of aligning the goals of an AI with human objectivesis difficult because of the black-box nature of neural networks. It is incredibly hard to know what is going on inside of an AI when its coming up with outputs. AI systems might develop their own goals that diverge from ours, which are challenging to detect and counteract.

For instance, a reinforcement learning model (another form of machine learning), controlling a boat in a racing game maximised its score by circling and collecting power-ups rather than finishing the race. Given its aim was to achieve the highest score possible, it will go about finding ways to do that even if it breaks our understanding of how to play the game.

It may seem far-fetched to argue that advanced AI systems could pose an existential risk to humanity based on this humorous example. However, if we entertain the idea that AI systems can develop goals misaligned with our intentions, it becomes easier to envision a scenario where an advanced AI system could lead to disastrous consequences for mankind.

Imagine a world where advanced AI systems gain prominence within our economic and political systems, taking control of or being granted authority over companies and institutions. As these systems accumulate power, they may eventually surpass human control, leaving us vulnerable to permanent disempowerment.

What do we do about this?

There is a growing field of professionals that are working in the field of AI safety, who are focused on solving the alignment problem and ensuring that advanced AI systems do not spiral out of control.

Presently, their efforts encompass various approaches, such as interpretability work, which aims to decipher the inner workings of otherwise opaque AI systems. Another approach involves ensuring that AI systems are truthful with us. A specific branch of this work, known as eliciting latent knowledge, explores the extraction of "knowledge" from AI systems, effectively compelling them to be honest.

At the same time, significant work is being carried out in the realm of AI governance. This includes efforts to minimise the risks associated with advanced AI systems by focusing on policy development and fostering institutional change. Organisations such as the Centre for Governance of AI are actively engaged in projects addressing various aspects of AI governance. By promoting responsible AI research and implementation, these initiatives seek to ensure that advanced AI systems are developed and deployed in ways that align with human values and societal interests.

The field of AI safety remains alarmingly underfunded and understaffed, despite the potential risks of advanced AI systems. Benjamin Hilton estimates that merely 400 people globally are actively working to reduce the likelihood of AI-related existential catastrophes. This figure is strikingly low compared to the vast number of individuals working to advance AI capabilities, which Hilton suggests is approximately 1,000 times greater.

If this has piqued your interest or concern, you might want to consider pursuing a career in AI safety. To explore further, you could read the advice provided by 80,000 Hours, a website that provides support to help students and graduates switch into careers that tackle the worlds most pressing problems, or deepen your understanding of the field of AI safety by enrolling in the AGI Safety Fundamentals Course.

Featured image: Generated using DALL-E by OpenAI

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Why we should be concerned about advanced AI - Epigram

Purdue President Mung Chiang made these remarks during the universitys Spring Commencement ceremonies May 12-14.

Opening

Today is not just any graduation but the commencement at a special place called Purdue, with a history that is rich and distinct and an accelerating momentum of excellence at scale. There is nothing more exciting than to see thousands of Boilermakers celebrate a milestone in your lives with those who have supported you. And this commencement has a special meaning to me as my first in the new role serving our university.

President Emeritus Mitch Daniels gave 10 commencement speeches, each an original treatise, throughout the Daniels Decade. I was tempted to simply ask generative AI engines to write this one for me. But I thought itd be more fun to say a few thematic words by a human for fellow humans before that becomes unfashionable.

AI at Purdue

Sometime back in the mid-20th century, AI was a hot topic for a while. Now it is again; so hot that no computation is too basic to self-anoint as AI and no challenge seems too grand to be out of its reach. But the more you know how tools such as machine learning work, the less mysterious they become.

For the moment, lets assume that AI will finally be transformational to every industry and to everyone: changing how we live, shaping what we believe in, displacing jobs. And disrupting education.

Well, after IBMs Deep Blue beat the world champion, we still play chess. After calculators, children are still taught how to add numbers. Human beings learn and do things not just as survival skills, but also for fun, or as a training of our mind.

That doesnt mean we dont adapt. Once calculators became prevalent, elementary schools pivoted to translating real-world problems into math formulations rather than training for the speed of adding numbers. Once online search became widely available, colleges taught students how to properly cite online sources.

Some have explored banning AI in education. That would be hard to enforce; its also unhealthy as students need to function in an AI-infused workplace upon graduation. We would rather Purdue evolve teaching AI and teaching with AI.

Thats why Purdue offers multiple major and minor degrees, fellowships and scholarships in AI and in its applications. Some will be offered as affordable online credentials, so please consider coming back to get another Purdue degree and enjoy more final exams!

And thats why Purdue will explore the best way to use AI in serving our students: to streamline processes and enhance efficiency so that individualized experiences can be offered at scale in West Lafayette. Machines free up human time so that we can do less and watch Netflix on a couch, or we can do more and create more with the time saved.

Pausing AI research is even less practical, not the least because AI is not a well-defined, clearly demarcated area in isolation. All universities and companies around the world would have to stop any research that involves math. My Ph.D. co-advisor, Professor Tom Cover, did groundbreaking work in the 1960s on neural networks and statistics, not realizing those would later become useful in what others call AI. We would rather Purdue advance AI research with nuanced appreciation of the pitfalls, limitations and unintended consequences in its deployment.

Thats why Purdue just launched the universitywide Institute of Physical AI. Our faculty are the leaders at the intersection of virtual and physical, where the bytes of AI meet the atoms of what we grow, make and move from agriculture tech to personalized health care. Some of Purdues experts develop AI to check and contain AI through privacy-preserving cybersecurity and fake video detection.

Limitations and Limits

As it stands today, AI is good at following rules, not breaking rules; reinforcing patterns, not creating patterns; mimicking whats given, not imagining beyond their combinations. Even individualization algorithms, ironically, work by first grouping many individuals into a small number of similarity classes.

At least for now, the more we advance artificial intelligence, the more we marvel at human intelligence. Deep Blue vs. Kasparov, or AlphaGo vs. Lee, were not fair comparisons: the machines used four orders of magnitude more energy per second! Both the biological mechanisms that generate energy from food and the amount of work we do per Joule must be astounding to machines envy. Can AI be as energy efficient as it is fast? Can it take in energy sources other than electricity? When someday it does, and when combined with sensors and robotics that touch the physical world, youd have to wonder about the fundamental differences between humans and machines.

Can AI, one day, make AI? And stop AI?

Can AI laugh, cry and dream? Can it contain multitudes and contradictions like Walt Whitman?

Will AI be aware of itself, and will it have a soul, however awareness and souls are defined? Will it also be T.S. Eliots infinitely suffering things?

Where does an AI life start and stop anyway? What constitutes the identity of one AI, and how can it live without having to die? Indeed, if the memory and logic chips sustain and merge, is AI all collectively one life? And if AI duplicates a humans mind and memory, is that human life going to stay on forever, too?

These questions will stay hypothetical until breakthroughs more architectural than just compounding silicon chips speed and exploding data to black-box algorithms.

However, if given sufficient time and as a matter of time, some of these questions are bound to eventually become real, what then is uniquely human? What would still be artificial about artificial intelligence? Some of that eventuality might, with bumps and twists, show up faster than we had thought. Perhaps in your generation!

Freedoms and Rights

If Boilermakers must face these questions, perhaps it does less harm to consider off switches controlled by individual citizens than a ban by some bureaucracy. May the medicine be no worse than the disease, and regulations by government agencies not be granular or static, for governments dont have a track record of understanding fast-changing technologies, let alone micromanaging them. Some might even argue that government access to data and arbitration of algorithms counts among the most worrisome uses of AI.

What we need are basic guardrails of accountability, in data usage compensation, intellectual property rights and legal liability.

We need skepticism in scrutinizing the dependence of AI engines output on their input. Data tends to feed on itself, and machines often give humans what we want to see.

We need to preserve dissent even when its inconvenient, and avoid philosopher kings dressed in AI even when the alternative appears inefficient.

We need entrepreneurs in free markets to invent competing AI systems and independently maximize choices outside the big tech oligopoly. Some of them will invent ways to break big data.

Where, when and how is data collected, stored and used? Like many technologies, AI is born neutral but suffers the natural tendency of being abused, especially in the name of the collective good. Todays most urgent and gravest nightmare of AI is its abuse by authoritarian regimes to irreversibly lock in the Orwellian 1984: the surveillance state oppressing rights, aided and abetted by AI three-quarters of a century after that bleak prophecy.

We need verifiable principles of individual rights, reflecting the Constitution of our country, in the age of data and machines around the globe. For example, MOTA:

My worst fear about AI is that it shrinks individual freedom. Our best hope for AI is that it advances individual freedom. That it presents more options, not more homogeneity. That the freedom to choose and free will still prevail.

Let us preserve the rights that survived other alarming headlines in centuries past.

Let our students sharpen the ability to doubt, debate and dissent.

Let a university, like Purdue, present the vista of intellectual conflicts and the toil of critical thinking.

Closing

Now, about asking AI engines to write this speech. We did ask it to write a commencement speech for the president of Purdue University on the topic of AI, after I finished drafting my own.

Im probably not intelligent enough or didnt trust the circular clichs on the web, but what I wrote had almost no overlap with what AI did. I might be biased, but the AI version reads like a B- high school essay, a grammatically correct synthesis with little specificity, originality or humor. Its so toxically generic that even adding a human in the loop to build on it proved futile. Its so boring that you would have fallen asleep even faster than you just did. By the way, you can wake up now: Im wrapping up at last.

Maybe most commencement speeches and strategic plans sound about the same: Universities have made it too easy for language models! Maybe AI can remind us to try and be a little less boring in what we say and how we think. Maybe bots can murmur: Dont you ChatGPT me whenever were just echoing in an ever smaller and louder echo chamber down to the templated syntax and tired words. Smarter AI might lead to more interesting humans.

Well, there were a few words of overlap between my draft and AIs. So, heres from both some bytes living in a chip and a human Boilermaker to you all on this 2023 Purdue Spring Commencement: Congratulations, and Boiler Up!

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Purdue President Chiang to grads: Let Boilermakers lead in ... - Purdue University

As markets brace for a likely recession ahead, investors search for cryptos that can survive market crashes. Uncertainty looms large over the Federal Reserves plans, elevating volatility across the board.

Against this backdrop, the crypto market stands to benefit as investors hunt for returns in a market that has exhibited an inverse correlation with traditional financial systems,

This phenomenon shows the best cryptos for portfolio diversification, drawing attention to those with high stability and security, low risk, and real-world applications.

Aspects such as smart contracts, cross-platform interoperability, and lightning-fast transaction speeds further pique the interest of both existing and potential investors.

In this evolving financial landscape, savvy investors are looking for resilient cryptos with low volatility and risk that not only withstand market turmoil but also offer valuable opportunities for diversification.

Source: Sittipong Phokawattana / Shutterstock.com

Bitcoin(BTC-USD) is the crown jewel of the crypto world, boasting a market cap of over $540 billion, representing nearly 50% of the entire sectors capital.

After a torrid 2022, the first quarter of the year has had BTC skyrocketing from $16,000 to a jaw-dropping $28,000. The recent lull in inflation hints at a shift in the Federal Reserves hawkish stance, fueling bullish sentiments.

BTCs unrivaled crypto liquidity allows investors to trade and convert profits into real-world currency seamlessly. With the step-changes during the pandemic, a sizeable amount of institutional capital is parked in BTC, further solidifying its bull case. Hence, with these interesting advantages, its no wonder why BTC continues to steamroll its competition.

Source: shutterstock.com/BT Side

Ethereum(ETH-USD) is the second most popular crypto in terms of market cap and often mirrors Bitcoins movements.

Its no surprise that it enjoyed a robust first quarter, soaring from $1,200 to a remarkable $1,800. The platforms sheer size and magnetic appeal to institutional investors make it a safe bet during heightened volatility.

The platform has been undergoing multiple changes, boosting scalability, security, and safety. It will introduce an innovative scaling solution called roll-ups that accelerate transactions while cutting user fees.

Its much-talked-about proto-dank sharding upgrade is expected to be launched in the second half of 2023, making transactions roughly 40 to 100 times cheaper.

The recent Shanghai fork has effectively laid the groundwork for brighter future ETH enthusiasts. These cutting-edge enhancements will further cement ETHs status as an industry trailblazer.

Source: Shutterstock

Cardano(ADA-USD) is arguably one of the most popular altcoins, which is nipping at BTCs heels in the race for year-to-date gains.

Conceived by Ethereum co-founder Charles Hoskinson, ADA boasts a wide variety of features similar to ETH, including a public blockchain platform, a robust proof-of-stake model, and enabling decentralized finance transactions.

Cardanos breakneck pace and powerful technology have helped it rise up the ranks of the hotly competitive crypto sphere. With its capabilities of handling one million transactions per second and minimal energy footprint, it has become one the top crypto picks of crypto investors.

With a slew of upgrades on the horizon, Cardano will bolster its security and enable seamless interconnectivity with other blockchains. Should these enhancements live up to expectations, we could witness a major rally in ADA.

Source: Rcc_Btn / Shutterstock.com

Solana(SOL-USD) is another dazzling altcoin that was one of the stand-out performers during the pandemic years.

However, like its peers, it shed a ton of value last year, dropping over 90% in value. Its been ticking in the green since the start of the year; the jury is still unsure whether Solana can sustain its upward trajectory throughout 2023.

Solana offers various applications, spanning decentralized finance, gaming, non-fungible tokens (NFT), and others. The Layer 1 blockchain network outperformed Ethereum multiple times in the past few years across all key crypto verticals.

Most recently, the platform announced its foray into the burgeoning artificial intelligence sector. Solana users can now effectively interact with the network using an open-source plugin for the AI chatbot, ChatGPT.

This development allows users to monitor wallet balances, transfer Solana-native tokens, and even scoop up NFTs. Also, it unveiled its crypto-centric smartphone, Saga, which will function as a dedicated wallet for digital currencies.

Source: sdx15 / Shutterstock.com

As one of the top Layer 2 scaling solutions, Polygon(MATIC-USD) swoops in to address the speed-related issues that impact first-generation crypto protocols such as Bitcoin and Ethereum.

It primarily caters to the Ethereum network and has emerged as a vital cog in the platforms machine. Its future hinges on Ethereums dominance and sluggish transaction speeds. Given the Ethereum networks current speeds, Polygon will remain relevant in the crypto sphere.

Polygon secured a whopping $450 million investment from Sequoia Capital in growing its network. The company spent $1 billion in 2021 and early 2022 to add new firms to its network and expand its offerings.

Though the bear market has dampened investor sentiment, a revived bull market could ignite another major lift-off. Likewise, if more projects flock to the Polygon network, the outlook for MATIC will be bullish.

Source: Zarko Prusac / Shutterstock.com

Dogecoin is certainly a fan-favorite in the crypto realm, but many would argue that it is both a blessing and a curse.

With a massive and loyal online community behind it, DOGE will remain relevant despite its risk.

Though it does not have the same utility as other cryptos mentioned in the article, Dogecoins status as a leading crypto cannot be argued with.

Throughout the year, DOGE has witnessed several days where daily values have increased by 10%, enticing investors to capitalize on long-term gains. It has become a magnet for speculative crypto enthusiasts who want to capture lofty gains fueled by volatility.

Furthermore, it boasts a daily liquidity volume of more than $230 million, roughly 24 hours preceding this article, further highlighting its appeal to investors seeking a dynamic crypto asset.

Source: Stanslavs / Shutterstock.com

Chainlink(LINK-USD) is another popular altcoin that is essentially a powerful blockchain network of oracles.

Oracles efficiently connect real-world data with decentralized systems. Chainlink is essentially revolutionizing the smart contract real by delivering critical data capacity to various blockchains.

Also, as a major catalyst for Web 3.0 development, the platforms dynamic exits optimize smart contract efficiency.

Effectively bridging the gap between on-chain and off-chain data sources, Chainlink provides crucial input for smart contracts.

Though the LINK token took hiding last year, its future gleams with promise. The token is up an impressive 30% since the years onset, showcasing the tokens long-term potential for growth and survival in unconducive markets.

Chainlinks spectacular progress signals its unwavering commitment to driving innovation in its sector.

On the date of publication, Muslim Farooque did not have (either directly or indirectly) any positions in the securities mentioned in this article.The opinions expressed in this article are those of the writer, subject to the InvestorPlace.comPublishing Guidelines

Muslim Farooque is a keen investor and an optimist at heart. A life-long gamer and tech enthusiast, he has a particular affinity for analyzing technology stocks. Muslim holds a bachelors of science degree in applied accounting from Oxford Brookes University.

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7 Must-Buy Cryptos That Can Survive Market Crashes - InvestorPlace

The decentralized Gala Games ecosystem has announced the launch of its Version 2 (V2) and the corresponding airdrop for all GALA Version 1 (V1) token holders. With the snapshot for the airdrop less than ten hours away, the token is rallying, yielding nearly 5% gains for holders overnight.

Also read: Lido Version 2 rollout on the Ethereum mainnet likely to be a sell-the-news event

GALAs Version 2 airdrop is scheduled to occur on Monday, as the games ecosystem prepares for the event. All holders of GALA V1 tokens will receive a 1:1 airdrop of the V2 token following the snapshot.

Gala Games ecosystem asked users to ensure that their V1 tokens are held in their private wallets or wallets of exchanges that support the Version 2 rollout.

Developers asked users to remove their GALA tokens from liquidity pools or smart contracts before snapshot on May 15 as there is no guarantee that tokens dropped to liquidity pool contracts will be recoverable.

Countdown to GALA V2 token snapshot

Ahead of the token airdrop, the protocols token yielded 5% gains for traders in a 24-hour timeframe. GALA price could correct in response to the airdrop, given the token has been rallying for a week in anticipation of the event.

If the event turns out to be sell-the-news, GALA price could pullback to support at $0.028.

GALA price is in a downtrend that started in February 2022. The token started its recovery in the beginning of 2023 with a 217% gain in the first week of January and 68% rally in the second week of March. With a definitive close above the descending trendline, GALA price could be poised for a similar price rally in May.

GALA/USD 1-day price chart

The immediate resistances are at $0.0592, $0.0879 and $0.1320, key levels for GALA throughout the second half of 2022. In the event of a decline, GALA price could nosedive to $0.0200, a level previously seen in the beginning of 2023.

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GALA price rallies 5% ahead of Version 2 tokens airdrop - FXStreet