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Dr. Amber Salzman, Ph.D. is Chief Executive Officer and Director of Epic Bio (https://epic-bio.com/), a fascinating therapeutic epigenome editing startup, developing therapies to modulate gene expression at the level of the epigenome, which just recently emerged from stealth mode with a $55 million funding round.

Dr. Salzman has more than 30 years of experience in the pharmaceuticals industry. Before joining Epic Bio, Dr. Salzman served as the president and CEO of Ohana Biosciences, pioneering the industry’s first sperm biology platform. Before Ohana, she served as the president and CEO of Adverum Biotechnologies and was a co-founder of Annapurna, SAS, where she served as President and CEO before its merger with Avalanche Biotechnologies to become Adverum. In that role, she saw the company’s stock price double.

Dr. Salzman began her career as a member of the GlaxoSmithKline (GSK) research and development executive team, where she was responsible for operations in drug development across multiple therapeutic areas, overseeing global clinical trials with over 30,000 enrolled patients, managing 1,600 employees and a $1.25B budget.

Following her time at GSK, Dr. Salzman served as the CEO of Cardiokine, a pharmaceutical company that developed treatments for the prevention of cardiovascular diseases and saw the successful sale of the company to Cornerstone Therapeutics.

Continue reading “Dr. Amber Salzman, PhD — CEO & Director, Epic Bio — Editing The Epigenome To Treat Complex Diseases” | >

Sandy and Cory discuss the evolution of Model 3 and Model Y bodies in white over the last five years. Sandy points out the massive advancements that have been made and encourages other OEMs to pursue similar efficiency and lean design.

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Continue reading “Giga Castings with Sandy | Evolution of Tesla Bodies In White” | >

KELT-9b is an ultra-hot Jupiter planet that orbits an A type star named KELT-9 about 650 light years away. The reason for this insane heat is the intimate proximity the gas giant has to its host star, which is itself among some of the hottest stars we know, reaching temperatures of roughly 9900ºC (17,852ºF).

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Researchers have found a way to use chaos to help develop digital fingerprints for electronic devices that may be unique enough to foil even the most sophisticated hackers.

Just how unique are these fingerprints? The researchers believe it would take longer than the lifetime of the universe to test for every possible combination available.

“In our system, chaos is very, very good,” said Daniel Gauthier, senior author of the study and professor of physics at The Ohio State University.

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A team of researchers from the National University of Singapore (NUS) has developed a novel technique that allows Physically Unclonable Functions (PUFs) to produce more secure, unique ‘fingerprint’ outputs at a very low cost. This achievement enhances the level of hardware security even in low-end systems on chips.

Traditionally, PUFs are embedded in several commercial chips to uniquely distinguish one from another by generating a secret key, similar to an individual fingerprint. Such a technology prevents hardware piracy, chip counterfeiting and physical attacks.

The research team from the Department of Electrical and Computer Engineering at the NUS Faculty of Engineering has taken silicon chip fingerprinting to the next level with two significant improvements: firstly, making PUFs self-healing; and secondly, enabling them to self-conceal.

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The ubiquity of electronic devices makes it essential to use encryption and anti-counterfeiting tools to protect the privacy and security of users. With the growing expansion of the Internet of Things, protection against attacks that violate the authenticity of products is increasingly necessary. Traditionally, message protection has been based on different systems: passwords, digital signatures or encryption. This cryptography is based on unknown keys to a possible attacker, but unfortunately these systems are becoming obsolete as new more invasive attacks appear: malware, API attacks or physical hardware attacks.

While quantum computing slowly progresses towards the cryptographic paradigm, the so-called physically unclonable functions (PUFs) are presented as the choice to ensure unique and effective identification. A PUF is a device that has unique and non-repeatable physical properties that can be translated into usable bits of information. The idea of applying random to identify systems or people is not new: for example, the identification of individuals using the fingerprint dates from the 19th century. More recently, the identity of electronic devices has been established using PUFs, which are “electronic fingerprints” of an integrated circuit.

Authentication based on PUFs comprises a chip manufactured by intrinsically random processes that make cloning almost impossible, even though all the details of the manufacturing process are known. The measurements of the various physical properties of the PUF depend on the properties of the chip at the nanoscale, thus constitute a very powerful anti-fraud and anti-counterfeiting technology. To be implementable at an industrial level, this chip must be low cost, scalable and its properties must be easily measurable by means of an identifiable function.

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To read about all our work on solving protein folding, go to deepmind.com/AlphaFold or read a timeline of the breakthrough here.

It’s been one year since we released and open sourced AlphaFold, our AI system to predict the 3D structure of a protein just from its 1D amino acid sequence, and created the AlphaFold Protein Structure Database (AlphaFold DB) to freely share this scientific knowledge with the world. Proteins are the building blocks of life, they underpin every biological process in every living thing. And, because a protein’s shape is closely linked with its function, knowing a protein’s structure unlocks a greater understanding of what it does and how it works. We hoped this groundbreaking resource would help accelerate scientific research and discovery globally, and that other teams could learn from and build on the advances we made with AlphaFold to create further breakthroughs. That hope has become a reality far quicker than we had dared to dream. Just twelve months later, AlphaFold has been accessed by more than half a million researchers and used to accelerate progress on important real-world problems ranging from plastic pollution to antibiotic resistance.

Today, I’m incredibly excited to share the next stage of this journey. In partnership with EMBL’s European Bioinformatics Institute (EMBL-EBI), we’re now releasing predicted structures for nearly all catalogued proteins known to science, which will expand the AlphaFold DB by over 200x — from nearly 1 million structures to over 200 million structures - with the potential to dramatically increase our understanding of biology.

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