As Principal Analyst for Collaboration and Conferencing at Current Analysis, Brad analyzes the rapidly expanding use of collaboration software and services as a means of improving business agility, fostering employee optimization and driving business opportunities.
Surprise! BlackBerry is no longer a languishing phone company struggling to remain relevant opposite powerhouse consumer hardware manufacturers Apple, Samsung, Google, et al.
Now a pure software developer with positive revenue numbers, the firm is embarking on an AI-powered journey of trusted and safe communications across a small number of very distinct but highly lucrative markets.
I have always had a soft spot for aging technology. I miss my clear case Apple Newton (stolen) and regret that I can no longer fire up my IBM ThinkPad 701 (the one with the butterfly keyboard). In honor of the 30th anniversary of the Nintendo Game Boy this past week, I even pulled out my Game Boy Pocket (also clear case) for a few rounds of Asteroids and Mortal Kombat II. And even though I never owned a BlackBerry phone, I miss the company’s long-standing dedication to the highly effective but now outdated concept of an actual, qwerty keyboard. Continue reading “Meet the New BlackBerry: Unique Potential Wrapped in the Enigma of AI, Smothered with Cybersecurity Sauce”→
What do Facebook’s ‘10-Year Challenge,’ Domino’s ‘Points for Pies’ app, and the early detection of diabetic retinopathy all have in common? They prove the difficulty in separating the peril from the promise of AI.
More importantly, however, they illuminate the need for an enforceable code of ethics that includes all ecosystem participants.
At its annual re:Invent 2018 conference, Amazon Web Services rolled out a blinding number of micro-specialized solutions that emphasize ‘best of need’ over ‘best of breed.’
But, there’s a danger lurking in this seeming freedom to adopt and combine capabilities at will, namely a new form of vendor lock-in.
At Amazon Web Services re:Invent 2018 this past week, attendees were treated to an avalanche of product launches and pre-release announcements. On display were three new data management services, four new Internet of Things (IoT) capabilities, eight new storage offerings, and thirteen new machine learning (ML) libraries — all designed to encourage developers to build and deploy solutions on the Amazon Web Services (AWS) platform. And that’s just the software dealing with big data and analytics. Continue reading “Amazon re:Invent 2018: Say Goodbye to Best-of-Breed and Hello to Best-of-Need Applications”→
• If blockchain is such a good idea, why hasn’t the enterprise IT industry already put it to work at scale?
• As it turns out, the reasons behind blockchain’s slow rate of adoption are as complex and multifaceted as blockchain itself.
Blockchain has been in the news recently with a number of notable players announcing the creation of advantageous partnerships, industry-savvy consortiums, and operationalized use cases. In just the last two days, systems integration powerhouse Accenture announced an innovative mechanism to connect disparate blockchain platforms, while IBM together with Telefónica announced a joint effort to use blockchain to streamline international call routing operations. Both investment and positive speculation remain at an all-time high for blockchain. Continue reading “Is the Idea of Blockchain Too Beautiful to Succeed?”→
• Data and analytics have historically belonged to the technological elite, those able to understand the subtleties of inner vs. outer database joins or those willing to learn the difference between a scatter plot and histogram.
• That’s about to change, thanks to a groundswell of innovations emerging from analytics vendors which promise to make data analysis as easy as asking Google Assistant for the day’s weather forecast.
Here’s a very simple proposition to consider: What if we don’t really need citizen data scientists or business-savvy data specialists to realize the current dream shared by most in the enterprise data and analytics marketplace — that dream being the true democratization of data and data-driven insights.
What if instead of asking data specialist to put together a static report — an often iterative and time consuming process — anyone in an organization could type out the simple question, “What were this quarter’s sales numbers?” and get back a timely and accurate data visualization of that quarter’s sales numbers. Continue reading “Tableau Conference 2018: Hello, This is Your Data Calling”→
• At its annual Connect conference in Shanghai, Huawei formally rolled out a new AI portfolio aptly marketed as a full-stack, all-scenario proposition that spans the physical and virtual AI solution set, covering everything from chip to solution.
• Somewhat lost in the sheer size of this portfolio, however, is a hidden gem that seeks to solve one of the biggest challenges facing AI practitioners, namely how to manage the lifecycle of AI apps themselves.
When Huawei sets its sights on a new market opportunity, rarely does the vendor tentatively dip its toes into unknown waters. As has become customary for the globally ambitious technology Chinese provider, new challenges are met all at once with an all-encompassing, all-inclusive portfolio of products that emphasizes immediate availability over future roadmap potentiality. And so it was this week when Huawei introduced its hyphen-heavy full-stack, all-scenario AI portfolio, that begins with the company’s new round of AI Ascend chips and ends with pre-integrated industry solutions.
• What can we learn from global server powerhouse Inspur about customizing servers in order to optimize demanding AI workloads?
• Using Inspur’s joint design and manufacturing (JDM) business model as a guide, it seems current server hardware and software architectures are leaning heavily in the direction of extreme customization, scale and agility.
Just as the promise of AI is very real and likely to significantly alter the way all markets do business, so too is the danger that the decisions we make based upon AI may be flawed, filled with unseen bias, or just plain wrong.
Recent, diverging solutions from IBM and Google to the problem of building trust in AI reveal the sheer magnitude of this multifaceted problem and point to a multi-pronged solution that starts on the drawing board and ends in practice.
Without a doubt, artificial intelligence (AI) has already changed the way consumers interact with technology and the way businesses think about big challenges like digital transformation. In fact, GlobalData research shows that approximately 50% of IT buyers have already prioritized the adoption of AI technologies. And that number is expected to jump to more than 67% over the next two years. Continue reading “How to Succeed in AI by Really, Really Trying”→
During its 4th annual analyst conference in Philadelphia, Comcast Business unveiled a new and decidedly inscrutable go-to-market campaign entitled “Beyond Fast.”
Plying its ActiveCore platform and virtualized network functions (VNFs), Comcast Business hopes to move beyond basic network functions and reach actual business outcomes not just for big business but also for its core SMB broadband customers.
When it comes to delivering connectivity to enterprise customers, Comcast Business doesn’t work (or think) like your typical telecom operator — or cable provider for that matter. For Comcast Business it isn’t about scaling up but rather scaling outward; it’s about delivering managed enterprise networking services the same way Comcast the cable provider delivers entertainment. That means standing up a huge number of endpoints in rapid succession. The company’s goal is to provision a new Ethernet customer every three minutes and add a new cable customer every 17 seconds.