Establishing trust in data is an essential requirement for businesses and entities for whom credible, reliable information is the lifeblood. As enterprises seek to manage data as an asset, it becomes increasingly vital that data sources are trusted and verifiable. I wrote a few weeks ago about the MIT initiative to establish a framework for trusted data, and the resulting position paper, "Towards an Internet of Trusted Data: A New Framework for Identity and Data Sharing". The authors highlight the criticality and need for "trustworthy, auditable data provenance" where "systems must automatically track every change that is made to data, so it is auditable and completely trustworthy". One of the key recommendations of the study was to improve the process and quality of data sharing.

AI startup Wave Computing announced this week that it has acquired MIPS Tech, Inc. (formerly MIPS Technologies), a global leader in RISC processor Intellectual Property (IP) and licensable CPU cores. The acquisition will accelerate Wave's strategy of offering AI acceleration from the Datacenter to the Edge of Cloud by extending the company's products beyond AI systems to now also include AI-enabled embedded solutions. This is a major milestone not only in the history of our two companies, but also for the AI compute industry," said Derek Meyer, CEO of Wave Computing. "With working DPU commercial silicon and being in the final stages of bringing our first AI systems to market, now is the time for us to expand to the Edge of Cloud. The acquisition of MIPS allows us to combine technologies to create products that will deliver a single'Datacenter-to-Edge' platform ideal for AI and deep learning.

Google has published a set of fuzzy but otherwise admirable "AI principles" explaining the ways it will and won't deploy its considerable clout in the domain. "These are not theoretical concepts; they are concrete standards that will actively govern our research and product development and will impact our business decisions," wrote CEO Sundar Pichai. The principles follow several months of low-level controversy surrounding Project Maven, a contract with the U.S. military that involved image analysis on drone footage. Some employees had opposed the work and even quit in protest, but really the issue was a microcosm for anxiety regarding AI at large and how it can and should be employed. Consistent with Pichai's assertion that the principles are binding, Google Cloud CEO Diane Green confirmed today in another post what was rumored last week, namely that the contract in question will not be renewed or followed with others.

Artificial intelligence keeps barreling forward, and of all the sectors it will likely impact, we ought to think through autonomous vehicles, criminal justice and the media sooner than later. Those are the first three areas that a new AI-centered philanthropic fund is engaging first. The fund formed early this year with a $27 million pool of donations from the Knight and Hewlett foundations, Reid Hoffman, the Omidyar Network, and investor Jim Pallotta. Now it's announced its first round of payouts. The main grantees won't be a surprise, as the Berkman Klein Center at Harvard and the MIT Media Lab are the anchor institutions, and will share $5.9 million.

On balance, there will be some jobs lost to artificial intelligence, and you can also expect AI to create other jobs. But at the global information services company Wolters Kluwer, AI is being infused into expert systems in a bid to augment lawyers, accountants, and other professionals with superior decision-making abilities. Dutch firm that provides knowledge management software and services to companies in the financial services, healthcare, tax and accounting, and legal arenas. The 180-year-old company originally encapsulated its knowledge and recommendations for specific professional domains in books, but today it has largely made the transition to digital technologies. Thousands of companies around the world rely on Wolters Kluwer's practice management software to automate core aspects of their businesses. That includes doctor's offices that use its software make healthcare decisions in a clinical setting, corporate law offices that use its software to understand M&A activities, and accounting firms that use its software to craft tax strategies for high net-worth clients.

In our Expert Takes, opinion leaders from inside and outside the crypto industry express their views, share their experience and give professional advice. Expert Takes cover everything from Blockchain technology and ICO funding to taxation, regulation, and cryptocurrency adoption by different sectors of the economy. If you would like to contribute an Expert Take, please email your ideas and CV to george@cointelegraph.com. According to TI's Corruption Perceptions Index for 2017, Spain slid eight points to be one of the EU's lowest ranked countries due to a spate of high-profile corruption scandals over the last decade -- with public procurement being particularly vulnerable. Albeit, Spain has been actively combating corruption by amending its anti-corruption laws and by developing blockchain and artificial intelligence (AI) solutions.

We are living in an age of disruption and one of the drivers of that change is a development that many people call Artificial Intelligence. It is a very broad heading under which many people seem to pin their hopes and fears. AI has been portrayed as an existential threat to humanity, or as just an excel sheet on steroids. Some, like Ray Kurzweil, point towards the Singularity when we reach real Artificial Intelligence. Just like a gravitational singularity where gravitational tidal forces become infinite this Singularity will be an Event Horizon- a point of no return -- a place and time which we can't see beyond.

Microsoft has publicly committed $50 million over 5 years for artificial intelligence projects that support clean water, agriculture, climate, and biodiversity. But our true vision extends beyond a grant program: our data science team is working with partners and nonprofits to build a set of APIs to transform these environmental issues. Imagine machine learning models exposed through services which could differentiate between various species of animal for conservation purposes, predict agricultural yields, estimate the probability of floods, super resolve climate predictions, or classify aerial and satellite imagery into actionable maps of natural resources that could empower land use planners to optimize the use of our planet's scarce resources. In this session, we will share an initial set of APIs in private preview, as well as demonstrate the process whereby additional APIs can be added to the growing portfolio of AI for Earth APIs. Join us to learn about APIs that could literally change the way society monitors, models, and ultimately manages Earth's life support systems.

Artificial intelligence is transforming the legal profession -- and that includes legal ethics. AI and similar cutting-edge technologies raise many complex ethical issues and challenges that lawyers ignore at their peril. At the same time, AI also holds out the promise of helping lawyers to meet their ethical obligations, serve their clients more effectively, and promote access to justice and the rule of law. What does AI mean for legal ethics, what should lawyers do to prepare for these changes, and how could AI help improve the legal profession? In some ways, nothing has changed.

With good reason, the general public has become increasingly wary about the sudden growth in artificial intelligence software, but another high-growth area of software--blockchain--could solve many of the issues holding back modern A.I. development and adoption. As a community, we must first acknowledge that real-world artificial intelligence has suffered from some rather spectacular public failures of late. Microsoft, one of the most technically advanced companies on the planet, saw its Tay A.I. chatbot turn racist almost immediately after its release in March of 2016. Meanwhile, Tesla recently admitted that a January 2018 crash was caused because its autopilot A.I. technology couldn't recognize a parked fire truck. In the two years between the Tay incident and the Tesla fire truck crash, A.I. has been required to accomplish more dangerous and complex work, without having shed its capacity for serious, unexpected failure.