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Heart failure is often identified only when the heart has already deteriorated. This is in large part because the cause is unknown for about 70% of people who experience heart failure.

Researchers at The Hospital for Sick Children (SickKids) have discovered that one of the earliest signs of is a change in how the produces , with findings offering a potential way to preempt heart failure before the heart begins to deteriorate.

Led by Dr. Paul Delgado-Olguín, a scientist in the Translational Medicine program, the research may also help to explain the diversity of causes underlying heart failure.

Architects urgently need to get to grips with the existential threat posed by AI or risk, in ChatGPT’s words, “sleepwalking into oblivion”, writes Neil Leach.

In the near future, architects may become a thing of the past. Artificial intelligence (AI) is quickly advancing to a point where it can generate the design of a building completely autonomously. With the potential to create designs faster and with more accuracy than ever before, AI has the potential to revolutionize the architecture industry, leaving traditional architects out of the equation. This could spell the end of the profession as we know it, raising questions of what the future holds for architects in a world of AI-generated buildings.

I did not write the paragraph above. It was generated by ChatGPT, a highly impressive AI text generator that recently launched. Make no mistake: despite its innocuous-sounding name, ChatGPT is no simple chat bot. It is based on GPT3, a massive Generative Pre-Trained Transformer (GPT) that uses Deep Learning to produce human-like text from user-inputted prompts.

ChatGPT has passed the gold-standard exam required to practice medicine in the US — amid rising concerns AI could put white-collar workers out of jobs.

The artificial intelligence program scored between 52.4 and 75 percent across the three-part Medical Licensing Exam (USMLE). Each year’s passing threshold is around 60 percent.

Researchers from tech company AnsibleHealth who did the study said: ‘Reaching the passing score for this notoriously difficult expert exam, and doing so without any human reinforcement, marks a notable milestone in clinical AI maturation.’

Dr. Craig Kaplan discusses Artificial Intelligence — the past, present, and future. He explains how the history of AI, in particular the evolution of machine learning, holds the key to understanding the future of AI. Dr. Kaplan believes we are on an inexorable path towards Artificial General Intelligence (AGI) which is both an existential threat to humanity AND an unprecedented opportunity to solve climate change, povery, disease and other challenges. He explains the likely paths that will lead to AGI and what all of us can do NOW to increase the chances of a positive future.

Chapters.
0:00 Intro.
0:22 Overiew & summary.
0:45 Antecedents of AI
1:15 1956: Birth of the field / Dartmouth conference.
1:33 1956: The Logic Theorist.
1:58 1986: Backprogation algorithm.
2:26 2016: SuperIntelligent AI / Alpha Go.
2:51 Lessons from the past.
3:59 Today’s “Idiot Savant” AI
4:45 Narrow vs. General AI (AGI)
5:15 Deep Mind’s Alpha Zero.
6:19 Demis Hassabis on Alpha Fold.
6:47 Alpha Fold’s amazing performance.
8:03 OpenAI’s ChatGPT
9:16 OpenAI’s DALL-E2
9:50 The future of AI
10:00 AGI is not a tool.
10:30 AGI: Intelligent entity.
10:48 Humans will not be in control.
11:16 The alignment problem.
11:45 Alignment problem is unsolved!
12:45 Likely paths to AGI
13:00 Augmented Reality path to AGI
13:26 Metaverse / Omniverse path to AGI
14:20 AGI: Threat AND Opportunity.
15:10 Get educated — books.
15:48 Get educated — videos.
16:20 Raise awareness.
16:44 How to influence values of AGI
17:52 No guarantees, we must do what we can.
18:47 AGI will learn our values.
19:30 Wrap up / contact info.

LINKS & REFERENCES
Contact:
@iqcompanies.
[email protected].

Websites.

Research in fundamental science has revealed the existence of quark-gluon plasma (QGP)—a newly identified state of matter—as the constituent of the early universe. Known to have existed a microsecond after the Big Bang, the QGP, essentially a soup of quarks and gluons, cooled down with time to form hadrons like protons and neutrons—the building blocks of all matter.

One way to reproduce the extreme conditions prevailing when QGP existed is through relativistic heavy-ion collisions. In this regard, particle accelerator facilities like the Large Hadron Collider (LHC) and the Relativistic Heavy Ion Collider have furthered our understanding of QGP with experimental data pertaining to such collisions.

Meanwhile, have employed multistage relativistic hydrodynamic models to explain the data, since the QGP behaves very much like a perfect fluid. However, there has been a serious lingering disagreement between these models and data in the region of low transverse momentum, where both the conventional and hybrid models have failed to explain the particle yields observed in the experiments.

Last summer, the gravitational wave observatory known as LIGO caught its second-ever glimpse of two neutron stars merging. The collision of these incredibly dense objects — the hulking cores of long-ago supernova explosions — sent shudders through space-time powerful enough to be detected here on Earth. But unlike the first merger, which conformed to expectations, this latest event has forced astrophysicists to rethink some basic assumptions about what’s lurking out there in the universe. “We have a dilemma,” said Enrico Ramirez-Ruiz of the University of California, Santa Cruz.

The exceptionally high mass of the two-star system was the first indication that this collision was unprecedented. And while the heft of the stars alone wasn’t enough to cause alarm, it hinted at the surprises to come.

In a paper recently posted to the scientific preprint site arxiv.org, Ramirez-Ruiz and his colleagues argue that GW190425, as the two-star system is known, challenges everything we thought we knew about neutron star pairs. This latest observation appears to be fundamentally incompatible with scientists’ current understanding of how these stars form, and how often. As a result, researchers may need to rethink years of accepted knowledge.

While the U.S. was busy celebrating the Super Bowl on Sunday night, Europeans had their own spectacle. Early Monday morning, a bright flash streaked across the skies over western Europe as an asteroid discovered just hours earlier made its impact with Earth’s atmosphere. The asteroid, dubbed Sar2667, was first detected on the evening of Feb. 12 by astronomer Krisztián Sárneczky in Hungary.

That’s the premise of Yi Zheng’s new invention. The associate professor of mechanical and industrial engineering at Northeastern has created a sustainable material that can be used to make buildings or other objects able to keep cool without relying on conventional cooling systems.

Circa: 2021


MIE Associate Professor Yi Zheng developed a “cooling paper” that could help cool the air in homes and businesses without the use of electricity.

Main photo: What if buildings could stay cool all on their own—no electricity required? That’s the premise of a new invention by Yi Zheng, associate professor of mechanical and industrial engineering at Northeastern. Photo by Ruby Wallau/Northeastern University.

Researchers in the US developed a new energy-based benchmark for quantum advantage and used it to demonstrate noisy intermediate-scale quantum (NISQ) computers that use several orders of magnitude less energy than the world’s most powerful supercomputer. Quantum computing is a branch of computer science that focuses on the development of technologies based on quantum theory principles.

Quantum computing solves problems that are too complex for classical computing by utilizing the unique properties of quantum physics. The question of whether a quantum computer can perform calculations beyond the reach of even the most powerful conventional supercomputer is becoming increasingly relevant as quantum computers become larger and more reliable. This ability, dubbed “quantum supremacy,” marks the transition of quantum computers from scientific curiosity to useful devices. Scientists predict that Quantum computing is better than supercomputers as it performs tasks a million times faster. Quantum computers can handle complex calculations easily because they are built based on quantum principles that go beyond classical physics.

Quantum computers and supercomputers are extremely powerful machines used for complex calculations, problem solving, and data analysis. While both have the potential to revolutionize computing technology, they have significant speed and capability differences. In 2019, Google’s quantum computer performed a calculation that would take the world’s most powerful computer 10,000 years to complete. It is the seed for the world’s first fully functional quantum computer, which will be capable of producing better medicines, developing smarter artificial intelligence, and solving cosmic mysteries. Theoretical physicist John Preskill proposed a formulation of quantum supremacy, or the superiority of quantum computers, in 2012. He dubbed it the moment when quantum computers can perform tasks that ordinary computers cannot. To quickly crunch large amounts of data and achieve a single result, supercomputers employ a traditional computing approach with multiple processors.