When Peter Diamandis took to the stage at Madrid's Palacio de Cibeles for the Audi Summit for Progress last Tuesday, WhatsApp had crashed and the Wi-Fi wasn't working properly. It was a blow to the audience's faith in technology, but Diamandis, the star speaker at the summit, was ready to counter this. The 61-year-old doctor and engineer from New York has blind faith in the power of innovation and science. Diamandis, who is the founder of Singularity University and a friend of tycoon Elon Musk, has set up a number of technology companies and written several books in which he predicts a future of abundance, longevity, flying cars and an exponential increase in resources. It's a vision that is hard to imagine in times of war, an energy crisis and growing fears of recession.

We are clearly shifting to an increasingly borderless workforce in the form of the networks of people who make a living that is dependent on a specific company but work without any formal employment agreement with said company. Every company's value chain consists not just of its own employees but millions of others including gig workers, contingent workers, partner employees and more. There is a greater need today than ever before to redefine an organization's systems to embrace this outer core. We are also dealing with increased human longevity which is creating new challenges of living and working that will require greater flexibility than ever before. Employees need the ability to go in and out of the traditional employee lifecycle, moving from the usual part-time and full-time arrangements to more fluid ones that allow them the flexibility of committing more sporadically while also making time for family, reskilling, the pursuit of a purpose or personal passion, and so on.

Researchers from Human Longevity, Inc. (HLI) have published a study in which individual faces and other physical traits were predicted using whole genome sequencing data and machine learning. This work, from lead author Christoph Lippert, Ph.D. and senior author J. Craig Venter, Ph.D., was published in the journal Proceedings of the National Academy of Sciences (PNAS). The authors believe that, while the study offers novel approaches for forensics, the work has serious implications for data privacy, deidentification and adequately informed consent. The team concludes that much more public deliberation is needed as more and more genomes are generated and placed in public databases. For the IRB approved study, 1,061 ethnically diverse people ranging in age from 18 to 82 participated by having their genomes sequenced to an average depth of at least 30x.

The authors believe that, while the study offers novel approaches for forensics, the work has serious implications for data privacy, deidentification and adequately informed consent. The team concludes that much more public deliberation is needed as more and more genomes are generated and placed in public databases. For the IRB approved study, 1,061 ethnically diverse people ranging in age from 18 to 82 participated by having their genomes sequenced to an average depth of at least 30x. Researchers also collected phenotype data in the form of 3D facial images, voice samples, eye and skin color, age, height, and weight. The team predicted eye color, skin color and sex with high accuracy, but other more complex genetic traits proved more difficult.

The only thing certain about the global economy is uncertainty. Thanks to political unrest, terrorist attacks, and the repercussions of Brexit, caution is the dominant mindset of investors in every market, according to the latest quarterly global report on venture capital trends published jointly by KPMG International and CB Insights. This is the fourth consecutive quarter where investors pulled back despite a total 27.4 billion invested across 1,886 deals--seven of which were in the 1 billion unicorn range. After a high at this time last year, the total number of deals declined an additional 6% from the first quarter of 2016. Although the percentage may appear incremental, startup and earlystage company growth are important to the global economy.

Insilico Medicine and Life Extension announced today an exclusive collaboration to identify novel biomarkers of human aging through the use of big-data analytics and AI, with the ultimate goal of discovery and formulation of nutrients to support health and longevity. Insilico Medicine* is a big-data analytics company specializing in applying advances in deep learning to discovery of biomarkers and drugs. Life Extension**, a Florida-based organization established in the early 1980s, is a dietary-supplement innovator dedicated to extending healthy human longevity. Insilico Medicine will focus on applying advanced signaling pathway activation analysis techniques and deep-learning algorithms to find nutraceuticals that mimic the tissue-specific transcriptional response of many known interventions and pathways associated with health and longevity. Life Extension will use this information to develop novel nutraceutical products to support health and longevity, such as "geroprotectors" -- precision natural organic small-molecule formulations that slow down or even reverse age-associated conditions and damage.

Machine learning algorithms are becoming greatly beneficial for drug development. According to a recent paper, 'Use of machine learning approaches for novel drug discovery', they can now be applied in several steps of the drug discovery methodology. These include'the prediction of target structure, prediction of biological activity of new ligands through model construction, discovery or optimization of hits, and construction of models that predict the pharmacokinetic and toxicological (ADMET) profile of compounds.' AstraZeneca's announcement today that they have joined forces with Human Longevity, a US sequencing and machine learning company, to sequence 2 million genomes is therefore not a surprise as such, but it does represent a step up in terms of the scale of such projects. AstraZeneca will be able to use Human Longevity's database of 1 million genomic and heath records alongside 500,000 DNA samples from their own clinical trials.

AstraZeneca's announcement today that they have joined forces with Human Longevity, a US sequencing and machine learning company, to sequence 2 million genomes is therefore not a surprise as such, but it does represent a step up in terms of the scale of such projects. AstraZeneca will be able to use Human Longevity's database of 1 million genomic and heath records alongside 500,000 DNA samples from their own clinical trials. The creation of this new database is likely to take as long as a decade, but the project will also include sequences from samples donated in the past 15 years.