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SEATTLE, Aug. 19, 2022 /PRNewswire/ -- The 15th annual Artificial General Intelligence (AGI) Conference opens today at Seattle's Crocodile Venue. Running from August 19-22, the AGI conference event includes in-person events, live streaming, and fee-based video accessand features a diverse set of presentations from accomplished leaders in AI research.

As the AGI community convenes, it continues to promote efforts to democratize AI access and benefits. To that end, several AGI-22 presentations will officially launch DRLearneran open source project to broaden AI access and innovation by distributing AI/Machine Learning code that rivals or exceeds human intelligence across a diverse set of widely acknowledged benchmarks. (Within the AI research community these Arcade Learning Environment [ALE] benchmark tests are widely accepted as a proxy for situational intelligence.)

"Until now, tools at this level in 'Deep Reinforcement Learning' have been available only to the largest corporations and R&D labs," said project lead Chris Poulin. "But with the open-source release of the DRLearner code, we are helping democratize access to state-of-the-art machine learning tools of high-performance reinforcement learning," continued Poulin.

Ben Goertzel, Chairman of the AGI Society and AGI Conference Series, contextualized DRLearner as well-aligned with the goals of the AGI conference. "Democratizing AI has long been a central mission, both for me and for many colleagues. With AGI-22 we push this mission forward by fostering diversity in AGI architectures and approaches, beyond the narrower scope currently getting most of the focus in the Big Tech world," Goertzel said.

DRLearner project presentations include:

"Open Source Deep Reinforcement Learning" General Interest Keynote presented by Chris Poulin, Project Lead. (Journalists Note: Poulin's initial keynote is scheduled for Sunday, August 21. On this day the AGI-22 Conference is open to the general public.)

"Open Source Deep Reinforcement Learning: Deep Dive" Technical Keynote by Chris Poulin and co-principal author Phil Tabor. (Monday, August 22)

"Demo of Open Source DRLearner Tool" Code Demo by co-author Dzvinka Yarish (Monday, August 22)

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Poulin also noted the importance of managing expectations on the benefits on what DRLearner will, and will not, provide in its initial Beta release: "Fully implementing this state-of-the-art ML capability requires considerable computational power on the cloud, so we advise implementors to maintain realistic expectations regarding any deployment". DRLearner's benefits could be substantial, however, for the numerous organizations who have substantial computing budgets: analytical insights, expanded research capability, and perhaps a competitive advantage. "And for those whose professional lives are focused on AGI, this is an exciting time, as DRLearner can enhance their neural network training efforts" Poulin said.

Drawing on his working experience with both US and Ukrainian computer scientists and software developers, Poulin assembled an international team of expert developers to complete the open-source project. (See more about 'DRLearner's International Dev Team' below.)

A final noteworthy addition, is that the work of Poulin et al was advised by Adria Puigdomenech Badia of DeepMind. "DRLearner provides a great implementation of reinforcement learning algorithms, specifically including the curiosity approach that we had pioneered at DeepMind," said Puigdomenech Badia. Poulin likewise had high praise for the DeepMind's prior "Agent 57" achievement: "Agent 57 was one of a limited number of implementations (at Deep Mind) that consistently beat human benchmarks. And due to the elegant simplicity of its particular design, and help of Adria, it was the best candidate to inspire our software implementation," Poulin said.

ON ARTIFICIAL GENERAL INTELLIGENCE & THE AGI CONFERENCE GOALS

The original goal of the AI field was the construction of "thinking machines"computer systems with human-like general intelligence. Given the difficulty of that challenge, however, AI researchers in recent decades have focused instead on "narrow AI"systems displaying intelligence regarding specific, highly constrained tasks. But the AGI conference series never gave up on this field's ambitious vision; and throughout its fifteen-year existence AGI has promoted the resurgence of broader research on "artificial intelligence"in the original sense of that term.

And in recent years more and more researchers have recognized the necessity and feasibility of returning to the original goals of the field. Increasingly, there is a call for a transition back to confronting the more difficult issues of "human level intelligence" and "artificial general intelligence (AGI)." AGI leaders are committed to continuing the organization's longstanding leadership roleby encouraging and exploring interdisciplinary research based on different understandings of intelligence.

Today, the AGI conference remains the only major conference series devoted wholly and specifically to the creation of AI systems possessing general intelligence at the human level, and ultimately beyond. By convening AI/ML researchers for presentations and discussions, AGI conferences accelerate progress toward our common general intelligence goal.

About the AGI-22 Conference: visit https://agi-conf.org/2022/

About the DRLearner Project: visit http://www.drlearner.org

About Chris Poulin: Poulin specializes in real-time prediction frameworks at Patterns and Predictions, a leading firm in predictive analytics and scalable machine learning. Poulin is also an Advisor at Singularity NET & Singularity DAO. Previously at Microsoft, Poulin was a subject-matter-expert (senior director) in machine learning and data science. He also served as Director & Principal Investigator of the Durkheim Project, a DARPA-sponsored nonprofit collaboration with the U.S. Veterans Administration. At Dartmouth College, Poulin was co-director of the Dartmouth Meta-learning Working Group, and IARPA-sponsored project focused on large-scale machine learning. He also has lectured on artificial intelligence and big data at the U.S. Naval War College. Poulin is co-author of the book Artificial Intelligence in Behavioral and Mental Health (Elsevier, 2015). Chris Poulin's LinkedIn Profile

About Ben Goertzel: Chairman of the AGI Society and AGI Conference Series, Goetzel is CEO of SingularityNET, which brings AI and blockchain together to create a decentralized open market for AIs. SingularityNET is a medium for AGI creation and emergence, a way to roll out superior AI-as-a-service to vertical markets, and a vehicle for enabling public contributions toand benefits fromartificial intelligence. In addition to AGI, Goetzel's passions include life extension biology, philosophy of mind, psi, consciousness, complex systems, improvisational music, experimental fiction, theoretical physics, and metaphysics. For general links to various of his pursuits present and past, see the Goetzel.org website. Ben Goetzel's LinkedIn Profile

About Adria Puigdomenech Badia: For the past seven years Badia has been at DeepMind, where he has specialized in the development of deep reinforcement learning algorithms. Examples of this include 'Asynchronous Methods for reinforcement learning' where he and Vlad Mnih (DeepMind) proposed A3C - 'Neural episodic control'. Badia's recent projects include 'Never Give Up' and 'Agent57' algorithms, addressing one of the most challenging problems of RL: the exploration problem.

DRLearner's International Dev Team:

Chris Poulin (Project Lead-US)Phil Tabor (Co-Lead-US)Dzvinka Yarish (Ukraine)Ostap Viniavskyi (Ukraine)Oleksandr Buiko (Ukraine)Yuriy Pryyma (Ukraine)Mariana Temnyk (Ukraine)Volodymyr Karpiv (Ukraine) Mykola Maksymenko (Advisor-Ukraine)Iurii Milovanov (Advisor-Ukraine)

For media inquiries about the DRLearner project, please contact:

Gregory PetersonArchetype Communicationsgpeterson@archetypecommunications.com

For general inquiries about the AGI-22 Conference, please contact:

Jenny CorlettApril Sixsingularitynet@aprilsix.com

SOURCE drlearner.org

Read more:
At Artificial General Intelligence (AGI) Conference, DRLearner is Released as Open-Source Code -- Democratizing Public Access to State-of-the-Art...

The average U.S. high school class has 30 students, according to research from theNational Council on Teacher Quality, and while each student learns in their own way, practice and specific feedback are repeatedly shown to be effective in modern classrooms. With interactive tools likepractice sets, students can receive one-to-one feedback and support without ever leaving an assignment. This saves the educators time, while also providing insight into students learning processes and patterns.

Achieving both aims at once sounds like a tall order, but adaptive learning technologies helpto do just that. Adaptive learning, a model where students are given customized resources and activities to support their unique learning needs, has been around for decades. However, applying advancing artificial intelligence technology opens up a new set of possibilities to transform the future of school into a personal learning experience.

Google for Educationrecently expanded its suite of adaptive learning tools using artificial intelligence, machine learning and user-friendly design to bring robust capabilities into the classroom.

For educators, adaptive learning technologies help boost instruction, reduce administrative burdens and deliver actionable insights into students progress. More time for planning and catch-up work would help alleviate teachers stress, according to anEdWeek Research Center survey.

For students, adaptive learning tech can deepen comprehension of instructional concepts and help them achieve their personal potential. Through interactive lessons and assignments, real-time feedback and just-in-time support, students can advance through lessons in ways that help increase the likelihood of success.

LEARN MORE:Discover how Google for Education supports students and teachers with CDWG.

When a student grasps a new concept, it can create a magical moment where they suddenly get it, says Shantanu Sinha, vice president and general manager of Google for Education. Ensuring that students get access to the right content or material at the right time is a critical part of making this happen.

By prioritizing students individual learning needs and adapting instruction accordingly, personal learning delivers various benefits, from a well-rounded learning experience to increased productivity, according toeducational publisher Pearson.

Practice setsoffer immediate, personal feedback, which is one of the best ways to keep students engaged. When students are on the right track, fast feedback helps them build confidence and celebrate small wins. When students struggle, real-time feedback helps to ensure they truly understand the material before advancing through a lesson.

Making these experiences interactive can dramatically improve the feedback loop for the student, says Sinha. The ability to see their progress and accuracy when working on an assignment, as well as helpful additional content, can guide students and help them learn.

For instance, Google for Education practice sets use AI to deliver encouragement and support the moment students need them. This includes hints, pop-up messages, video lessons and other resources.

Click the bannerbelow to find resources from CDW to digitally transform your classroom.

With practice sets, teachers can build interactive assignments from existing content, and the software automatically customizes support for students. Practice sets also grade assignments automatically, with the AI recognizing equivalent answers and identifying where students go off track. All these capabilities help teachers extend their reach and maximize their time.

Practice sets also leverage AI to provide an overview of class performance and indicate trends. If several students are having trouble with a concept, teachers can see patterns and adjust quickly without manually sorting through students results.

AI-driven technology opens new opportunities for flexible teaching and learning options. OnChromebooks, for instance, teachers can use Screencast to record video lessons. AI transcribes the spoken lessons into text, allowing students to translate those transcripts into dozens of languages.

Googles adaptive learning tools have built-in, best-in-class security and privacy to protect students and educators personal information. Transparency, multilayered safeguards and continuous updates to ensure compliance with new legislation and best practices are central to delivering adaptive instruction that is secure.

Educators can see and manage security settings on Chromebooks andGoogle Workspacefor Education. IT administrators have visibility via Google for Educations Admin Console.

LEARN MORE:How can a Google Workspace for Education audit benefit your K12 district?

Screencast onChrome OSand practice sets inGoogle Classroomare Googles newest offerings in adaptive learning. Other useful tools include:

As adaptive learning technology continues to evolve, it has the potential to transform the learning experience and help teachers better meet students where they are in the learning journey. When the right technology is applied to teaching and learning, teachers and students can go further, faster.

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Google's Adaptive Learning Technologies Help Amplify Educators' Instruction - EdTech Magazine: Focus on K-12

Mon, Aug 22nd 2022 11:20 am

New book co-written by UB philosopher claims AI will never rule the world

AI that would match the general intelligence of humans is impossible, says SUNY Distinguished Professor Barry Smith

By the University at Buffalo

Elon Musk in 2020 said that artificial intelligence (AI) within five years would surpass human intelligence on its way to becoming an immortal dictator over humanity. But a new book co-written by a University at Buffalo philosophy professor argues that wont happen not by 2025, not ever!

Barry Smith, Ph.D., SUNY Distinguished Professor in the department of philosophy in UBs College of Arts and Sciences, and Jobst Landgrebe, Ph.D., founder of Cognotekt, a German AI company, have co-authored Why Machines Will Never Rule the World: Artificial Intelligence without Fear.

Their book presents a powerful argument against the possibility of engineering machines that can surpass human intelligence. Machine learning and all other working software applications the proud accomplishments of those involved in AI research are for Smith and Landgrebe far from anything resembling the capacity of humans. Further, they argue that any incremental progress thats unfolding in the field of AI research will in practical terms bring it no closer to the full functioning possibility of the human brain.

Smith and Landgrebe offer a critical examination of AIs unjustifiable projections, such as machines detaching themselves from humanity, self-replicating, and becoming full ethical agents. There cannot be a machine will, they say. Every single AI application rests on the intentions of human beings including intentions to produce random outputs. This means the Singularity, a point when AI becomes uncontrollable and irreversible (like a Skynet moment from the Terminator movie franchise) is not going to occur. Wild claims to the contrary serve only to inflate AIs potential and distort public understanding of the technologys nature, possibilities and limits.

Reaching across the borders of several scientific disciplines, Smith and Landgrebe argue that the idea of a general artificial intelligence (AGI) the ability of computers to emulate and go beyond the general intelligence of humans rests on fundamental mathematical impossibilities that are analogous in physics to the impossibility of building a perpetual motion machine. AI that would match the general intelligence of humans is impossible because of the mathematical limits on what can be modeled and is computable. These limits are accepted by practically everyone working in the field; yet they have thus far failed to appreciate their consequences for what an AI can achieve.

To overcome these barriers would require a revolution in mathematics that would be of greater significance than the invention of the calculus by Newton and Leibniz more than 350 years ago, says Smith, one of the worlds most cited contemporary philosophers. We are not holding our breath.

Landgrebe points out that, As can be verified by talking to mathematicians and physicists working at the limits of their respective disciplines, there is nothing even on the horizon which would suggest that a revolution of this sort might one day be achievable. Mathematics cannot fully model the behaviors of complex systems like the human organism, he says.

AI has many highly impressive success stories, and considerable funding has been dedicated toward advancing its frontier beyond the achievements in narrow, well-defined fields such as text translation and image recognition. Much of the investment to push the technology forward into areas requiring the machine counterpart of general intelligence may, the authors say, be money down the drain.

The text generator GPT-3 has shown itself capable of producing different sorts of convincing outputs across many divergent fields, Smith says. Unfortunately, its users soon recognize that mixed in with these outputs there are also embarrassing errors, so that the convincing outputs themselves began to appear as nothing more than clever parlor tricks.

AIs role in sequencing the human genome led to suggestions for how it might help find cures for many human diseases; yet, after 20 years of additional research (in which both Smith and Landgrebe have participated), little has been produced to support optimism of this sort.

In certain completely rule-determined confined settings, machine learning can be used to create algorithms that outperform humans, Smith says. But this does not mean that they can discover the rules governing just any activity taking place in an open environment, which is what the human brain achieves every day.

Technology skeptics do not, of course, have a perfect record. Theyve been wrong in regard to breakthroughs ranging from space flight to nanotechnology. But Smith and Landgrebe say their arguments are based on the mathematical implications of the theory of complex systems. For mathematical reasons, AI cannot mimic the way the human brain functions. In fact, the authors say that its impossible to engineer a machine that would rival the cognitive performance of a crow.

An AGI is impossible, says Smith. As our book shows, there can be no general artificial intelligence because it is beyond the boundary of what is even in principle achievable by means of a machine.

See the rest here:
Terminator? Skynet? No way. Machines will never rule the world, according to book by UB philosopher - Niagara Frontier Publications

For Donald Trumps critics, his Mar-a-Lago scandal has brought to mind the mess surrounding Hillary Clintons emails, and for good reason. Republicans and much of the political world spent years treating the Democrats email server protocols as one of the defining controversies of the era with many on the right calling for her prosecution for allegedly mishandling classified information.

Six years later, its the Republican who called for Clinton to be locked up who stands accused of mishandling classified national security information he took and wouldnt give back.

But in an unexpected twist, its Trumps allies who are also bringing up the story surrounding Clintons emails though the right doesnt appear to remember it quite as well as it should.

The Hill had this report, for example, on Florida Gov. Ron DeSantis speaking at a far-right gathering earlier this week.

And you look at the raid and Mar-a-Lago, and Im trying to remember, maybe someone here can remind me about when they did a search warrant at Hillarys house in Chappaqua when she had a rogue server and she was laundering classified information, [the governor said].

DeSantis added, I dont remember them doing that. The point, of course, was to suggest that federal law enforcement treated Clinton with kid gloves, while being vastly more aggressive toward Trump.

But there are a few problems with the story the Florida governor was trying to remember. For one thing, the FBI didnt raid Mar-a-Lago. For another, Clinton didnt launder any secrets. While were at it, there was no need to execute a search warrant to obtain emails, since they werent printed out, and unlike Trump, the former secretary of state didnt make any effort to obstruct federal officials efforts.

But most importantly, the detail DeSantis conveniently overlooked was the fact the FBI, as part of its investigation into Clinton, really did take her email server. (A search warrant wasn't necessarily because the former cabinet secretary, unlike the former Republican president, voluntarily turned over what the FBI was looking for.)

As it turns out, DeSantis isnt the only one whos a little forgetful about the story the GOP claimed to care so much about. His fellow Florida Republican, Rep. Michael Waltz, told Fox News this week that Trump, after taking office, made a conscious choice to leave his 2016 opponent alone.

President Trump took that approach. He said, You know what, were not going to prosecute Hillary Clinton, Waltz said, as if reality had no meaning. The congressman added, [Trump] said, You know what, lets move on. Lets move forward. But they are just incapable of doing it when it comes to him.

For those of us who were awake during Trumps presidency, the truth is that the Republican repeatedly lobbied the Justice Department to prosecute Clinton, even as late as October 2020. He also reveled in lock her up chants before, during, and after holding office.

The idea that the former president magnanimously decided to give the Democrat a pass and moved on from the email flap is utterly bonkers and the exact opposite of what actually happened.

Perhaps most amazing of all was Republican Rep. Markwayne Mullin of Oklahoma who complained late last week that there was no media frenzy when Clinton kept 33,000 classified emails on her server.

In reality, there were 113 emails, and Mullin was only off by 32,887. As for the lack of media frenzy, Im not sure how much more news organizations couldve obsessed over Clintons controversy. Shortly before Election Day 2016, Gallup asked voters what word they most closely associated with the former secretary of state, and emails dominated to an almost cartoonish degree.

That was, of course, the result of relentless media coverage. The year after the election, Columbia Journalism Review found that between October 29, 2016, and November3, 2016 a six-day span that included early voting in much of the country the New York Times published as many cover stories about Hillary Clintons emails as it did about all policy issues combined in the 69 days leading up to the election.

Taken together, Republicans have spent the last several days arguing that the Justice Department largely gave Clinton a pass; Trump chose to leave Clinton alone; and the media downplayed the significance of the entire Clinton email mess.

None of these claims reflects reality in any way and the most charitable explanation is that the same GOP voices who were obsessed with the email controversy just dont recall the events as well as one might expect given the circumstances.

Steve Benen is a producer for "The Rachel Maddow Show," the editor of MaddowBlog and an MSNBC political contributor. He's also the bestselling author of "The Impostors: How Republicans Quit Governing and Seized American Politics."

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GOP focuses on the Hillary Clinton email mess it doesn't remember - MSNBC

Remember when Donald Trump was running for president the first time and, outside of declaring Mexicans rapists and criminals, devoted his entire campaign to calling for Hillary Clinton to be prosecuted and sent to prison for her emails? And regularly encouraged the lock her up chants from his supporters? And told his opponent, at the second presidential debate, that if he was in charge of the country youd be in jail? His son-in-law, Jared Kushner, would like people to know that after winning the election, he tried to be friends with HRC but she blew it.

The Hill reports that in his new memoir, Breaking History, which was described this week by The New York Times as nausea-inducing and like watching a cat lick a dogs eye goo, Kushner writes that the most divisive president in US history genuinely wanted to help the country unite in the days following the 2016 election. As such, Trump supposedly tasked Ivanka Trump with getting in touch with Chelsea Clinton to arrange a get-together with Bill and Hillary. The Ivanka outreach, Kushner says, was meant to convey that Trump had no intention of looking backward and hoped to have a cordial relationship with Hillary to unite the country. Recalls the former first son-in-law: He even told Ivanka to invite Hillary and Bill for dinner in the coming weeks.

What, pray tell, would Trump have said at this dinner, in order to convey that he was willing to bury the hatchet he spent the entire campaign swinging at Hillarys head? Kushner doesnt get into details but presumably something along the lines of, Hillary, you lost really, really big. And even though people, many people, are saying I should throw you in prison, which would be my right as King of America, Im not going to do that. Youre welcome, Hillary.

Unfortunately, as it turns out, that dinner never came to pass. While Kushner claims that Ivanka did make the call to Chelsea, days later Hillary backed [Green Party presidential nominee] Jill Steins challenge to the election, and Trump ended his outreach. Then he proceeded to spend the next six years insisting that Clinton was a criminal, a theme that got plenty of airtime during his second run for the White House, despite Hillary not actually being his opponent.

Rudy Giuliani: Trump didnt steal classified documents, he was just holding onto them for safekeeping

Read more:
Jared Kushner Says Trump Wanted to Bury the Hatchet With Hillary Clinton After Spending All of 2016 Calling for Her Imprisonment - Vanity Fair