Oil prices have fallen dramatically over last few years, forcing some major oil companies to take drastic actions such as layoffs, cutting investments and budgets, and more. In view of falling oil prices and the resulting squeeze on cash flows, the oil and gas industry has been challenged to adapt and optimize its performance to remain profitable while maintaining a long-term investment and operating outlook. Currently, oil and gas companies find it difficult to maintain the same level of investment in exploration and production as when crude prices were at their peak. Operations in the oil and gas industry today means balancing a dizzying array of trade-offs in the drive for competitive advantage while maximizing return on investment. The result is a dire need to optimize performance and optimize the cost of production per barrel.

The success of artificial intelligence (AI) algorithms hinges on the ability to gain easy access to the right kind of data in sufficient volume. Put more simply, AI depends on good data. Even Google--which is famous for the pioneering work in AI that underpins its standard-setting search-based advertising business--makes no bones about the critical role of data in AI. Peter Norvig, Google's director of research, has said: "We don't have better algorithms, we just have more data." Companies increasingly realize that data is critical to their success--and they are paying striking sums to acquire it. Microsoft's US$26 billion purchase of the enterprise social network LinkedIn is a prime example. But other technology companies are also seeking to acquire data-related assets, typically to acquire more than just identity-linked information from social media sources by focusing instead on vast troves of anonymized consumer data. Think, for example, of Oracle pursuing an M&A-led strategy for its Oracle Data Cloud data aggregation service, or IBM buying, within the past two years, both The Weather Company and Truven Health Analytics. Early returns for companies making such investments are promising. Still, to unlock the full value of AI algorithms, companies must have access to large data sets, apply abundant data-processing power, and have the skills to interpret results strategically.

Strong interim results posted by Chinese smartphone camera makers may have proven yet again the future of camera manufacturing lies with lenses that are minuscule and A.I.-savvy. The landscape of the camera making industry has fundamentally changed as consumers are shelving their professional cameras and using smartphones to take pictures in recent years. Now as computer vision technology, which uses deep learning scheme to enable machines to understand digital images and videos, matures, smartphone camera makers, many of which are leading the pack in computer vision software development, could displace traditional camera makers' dominance in their own backyard. Companies such as Q Technology, Sunny Optical exemplified the rapid growth of smartphone camera makers in China. Both companies have posted strong first-half results this year, as traditional camera makers such as Canon see a decline in unit sales in digital compact cameras.

A revolution is happening right before our eyes. It's groundbreaking, and yet its disruptive power is only fractionally visible. With each passing second and each bit of new data, computers are getting smarter and smarter. Ubiquitous and quiet, machine learning algorithms are watching us, gathering information about our preferences, lifestyle, and habits. Consciously or unconsciously, we feel the benefits of these algorithms while lazing on our couches, clicking away on insightful recommendations for which movies to watch, books to read, and products to buy.

New drone footage has revealed the latest look of Tesla's Gigafactory located on Electric Avenue in Sparks, Nevada. Once completed in 2020, the factory is set to become one of the biggest buildings in the world, with a final size of 10 million square feet. With production underway at the Gigafactory, the company is churning out lithium ion battery cells by the masses in hopes to ultimately reduce the cost of sustainable energy. Tesla says the factory will be producing 35 gigawatt hours of batteries by 2018, which is crucial for the company in reaching its production target of 10,000 units per week in 2018 for its new Model 3 car. According to electrek, Tesla's goal is on target as Tesla co-founder Elon Musk said this month that the factory is already the biggest battery producing factory in the world.

In late June, BlackBerry reported quarterly earnings that missed analysts' forecasts due to an unexpected sales decline, ramping up pressure on the company to meet its goal of boosting software and services revenue by 10 percent to 15 percent this year. BlackBerry declined to comment on the stock price, but QNX manager Grant Courville said it expected to sign deals with at least three major companies to get QNX into self-driving vehicles.

Everyone who follows the tech space knows that artificial intelligence ("AI") is one of the hottest area of investment. From my anecdotal experience, if you ask market participants to list who they think is the current leader in AI, most will say Google (NASDAQ:GOOGL) (GOOG), then followed by perhaps Microsoft (MSFT) or NVIDIA (NVDA). Being labeled an "AI" company helps these stocks attract incremental investors. However, it surprises me how few market participants recognize Amazon's (AMZN) leadership in AI. In my view, though impossible to quantify exactly, Amazon's AI investments and capabilities should sustain and increase its competitive advantage over time, leading me to believe that the stock has a much longer runway than what investors are giving it credit for. If I am correct, this also means bad news for Amazon competitors - this is particularly true in the retail space where competitive have invested little in AI technology by comparison.

The Apple HomePod is slated to come out later this year, but it might be difficult to find on store shelves. Limited shipments at launch may give the Siri-powered home speaker a gradual rollout, according to the Nikkei Asian Review. During an earnings conference call Monday, HomePod supplier Inventec Appliances gave further details about the new Apple device's launch schedule. Inventec president David Ho said via the Review that the company is expecting to have a smaller amount of units when the HomePod launches this fall. "We will finally ship the smart home device this year, but its contribution will be fairly limited and hopefully that will improve next year."

ARMONK, New York - 08 Aug 2017: While marketing and sales professionals increasingly find themselves drowning in data, a new IBM (NYSE: IBM) study finds that nearly two thirds--64 percent--of surveyed CMOs and sales leaders believe their industries will be ready to adopt cognitive technologies in the next three years. However despite this stated readiness, the study finds that only 24 percent of those surveyed believe they have strategy in place to implement these technologies today. Surveyed executives from businesses that have outperformed their competition for the past three years in revenue growth, profitability, or other factors, made up 13 percent of the study. Of these surveyed Outperformers, 93 percent believe cognitive computing is mature and market ready, and 91 percent assert that cognitive computing is good for their organizations. Cognitive computing, such as IBM Watson, is a next generation technology that can quickly understand and reason vast amounts of structured and unstructured data, like sounds and images, in the same way humans do--by reasoning, learning, and interacting to improve accuracy overtime.

Tableau, a Seattle-based business intelligence and analytics provider, announced this morning that it has acquired ClearGraph. Based in Palo Alto, Calif., ClearGraph provides smart data discovery and data analysis natural language query solutions. The purchase price has not been disclosed. ClearGraph was founded in 2014 by investment specialist Andrew Vigneault (CEO) and CTO Ryan Atallah. It is expected that ClearGraph's entire team will join Tableau and help integrate the technologies.