Tl;dr - has this idea about neural network architecture, similar to autoencoders, been developed already? Correct me if I'm wrong about anything, but this is my understanding so far: Autoencoders purposefully have an information bottleneck in the middle, and this bottleneck is what forces the network to learn high level representations of the input data. Otherwise, without the bottleneck, the network may discover that the optimal connection is one that is roughly equivalent to directly mapping each input to its corresponding output. However, because that bottleneck exists, it is very unlikely that an autoencoder could perform a perfect reconstruction of the input. Contrast this with other encoding, like DCT as used by JPEG images.

The application of machine learning to predictive analytics continues apace as a way to improve IT operations, data security and business intelligence. Among those offering frequent platform upgrades is real-time "operational intelligence" specialist Splunk Inc., which this week rolled out the latest versions of its IT, security and analytics packages that seek to "operationalize" machine data. San Francisco-based Splunk (NASDAQ: SPLK) said machine learning is integrated as a core capability in its latest package of IT, security and analytics offerings in the form of packaged or custom algorithms intended to leverage growing volumes of machine data. Use cases for its enterprise, IT services, security and user behavior analytics products include: "focused investigation" of IT and security incidents to detect data patterns and anomalies; reducing "alert fatigue" by identifying normal patterns for specific use cases; proactive maintenance; demand forecasting, managing inventory; and adjusting to changing business conditions by analyzing historical data. "The enterprise machine data fabric is the foundation for managing and deriving insights from that data at scale," Splunk President and CEO Doug Merritt asserted in a statement.

This week at Microsoft Ignite, we showed how we are infusing artificial intelligence (AI) broadly across Microsoft to help our customers. Our approach to this fundamental shift is to democratize AI and to make it accessible and valuable to everyone. We're focused on building an AI stack spanning infrastructure, services, apps and agents and reaching key customer audiences -- consumers, enterprises, developers. We are creating tools to make it easier for busy professionals to remember their commitments, family members from other countries to talk to each other in spite of language barriers, and multitasking smartphone users to send texts more quickly. And at the same time, we also are providing businesses with the tools they need to incorporate intelligence into every product they build and business decision they make.

The Partnership on AI consolidates control for a handful of corporations and their stakeholders, pitting them against Elon Musk's OpenAI open source, non-profit that is available to everyone. Both the Partnership on AI and Elon Musk's OpenAI were established to advance humanity through Artificial Intelligence. While Musk's OpenAI was devised to be open and available to the public, the Partnership on AI is more of a consolidation of power that benefits stakeholders whose findings will later be used to enact public policies. Google/DeepMind, Microsoft, Facebook, IBM, and Amazon have collaborated to form the Partnership on AI to "formulate best practices on the challenges and opportunities within the field." While third-party groups such as academics, non-profits, and policy specialists have been invited to be on the new Board of Directors, the Partnership on AI ultimately serves the private stakeholders, and whatever the stakeholders dictate will be relayed to the public.

Microsoft, Google, Facebook, Amazon, IBM and other tech companies have joined forces to democratise artificial intelligence (AI) and make it available for everyone. But what are their real motives? The AI world is exploding. It's called the Partnership on AI to benefit People and Society. Sounds lofty and earnest, but these are businesses after all.

The world's top tech firms, including Google's DeepMind, Facebook and Amazon, have formed the tech equivalent of a musical supergroup, joining forces to ensure the ethical development of artificial intelligence and "advance public understanding" of the technology which is increasingly working its way into our lives. The group, Partnership on AI, will connect academics, policy experts, and non-profits alongside businesses, which also include Microsoft and IBM, to hot house best practice in the burgeoning technology being used to help solve world health problems and reduce energy consumption - an industry expected to be worth 9.2bn by 2019. "The objective of the Partnership on AI is to address opportunities and challenges with AI technologies to benefit people and society," the group said, outlining its goals. "Together, the organisation's members will conduct research, recommend best practices, and publish research under an open license in areas such as ethics, fairness, and inclusivity; transparency, privacy, and interoperability; collaboration between people and AI systems; and the trustworthiness, reliability, and robustness of the technology. It does not intend to lobby government or other policymaking bodies." The five tech groups will fund the project as well as provide resources for research and expects more experts and groups working on AI technology to join the partnership in future.

Five of the world's largest technology companies have come together to shed light on the ongoing development of artificial intelligence. The entities involved are Facebook, Google and its DeepMind subsidiary, Amazon, Microsoft, and IBM, and the group's new nonprofit organization will grow to include a number of AI research groups and academics. Announced today, the coalition will be known as the Partnership on AI and it will be co-chaired by Microsoft Research chief Eric Horvitz and DeepMind co-founder Mustafa Suleyman. Apple is in talks with the group, but has not yet decided to join the organization. The partnership has two main focuses.

Microsoft has formed a new artificial intelligence research and development initiative that brings together 5000-plus computer scientists and engineers to realise the tech giant's AI vision. Fronted by Microsoft-alumni Harry Shum, the new division will be tasked with making AI accessible and valuable for'every person and organisation', building on the company's focus on AI across apps, services and infrastructure. The news comes hot on the heels of the launch of the Partnership on AI, the cross-industry collaboration between IBM, Microsoft, Google, Facebook and Amazon. The new group will unite existing Microsoft teams including Information Platform, Cortana, Bing and robotics. Its scope will include all AI product engineering and the company is taking a four-pronged approach to the initiative.

General Motors Co.'s Cruise Automation autonomous vehicle software start-up now has 100 employees, up from 40 when GM acquired it, GM Chairman and CEO Mary Barra said Thursday. Romulus -- General Motors Co.'s Cruise Automation autonomous vehicle software start-up now has 100 employees, up from 40 when GM acquired it, GM Chairman and CEO Mary Barra said Thursday. Barra, who was a keynote speaker at the World Mobility Leadership Forum held at Detroit Metro Airport, said people want to work on something that will be commercialized. "That's been one of the reasons that we've been able to grow this very specific type of resource of software artificial intelligence machine learning type of skill set and attract the talent because they see General Motors' commitment," Barra said. GM announced in March that it would buy Cruise Automation, a San Francisco-based software company that it hopes will quicken its development of autonomous vehicle technology.

International Business Machines Corp. plans to purchase consultancy Promontory Financial Group LLC., the two companies said Thursday, creating a new subsidiary dubbed'Watson Financial Services.' The companies didn't disclose financial details of the deal, which they said is subject to regulatory approvals. The idea, they said, is to combine Promontory's financial regulatory expertise with Watson, IBM IBM 0.61 % 's artificial intelligence computer system, to help banks meet ever-rising regulatory expectations in areas such as anti-money-laundering detection systems, consumer complaint databases, and so-called stress tests. Financial regulatory requirements are "rapidly outstripping the capacity of humans to keep up," a joint press release from the companies said. Privately held Promontory was founded in 2001 by Eugene Ludwig, a former U.S. Comptroller of the Currency, and has hired a small army of former regulators and government officials to advise financial firms.