Why you should be all in on Gen-AI

It’s been a while since I’ve written about a sea change in technology.  I think one of the last topics was the rise of Big-Data where collection, analysis and compute resources were all coming together to fuel a revolution in predictive analytics which we all take for granted today. For instance, we get upset when Google maps doesn’t re-route us even when the backup just happened.  Or how we now run genomic sequences on our dogs.

We’ve been spoiled. 

I’m now seeing the same momentum, hype, and emerging reality around Gen-AI both for large language models and Image-AI.   We stand on the cusp of Gen-AI changing the way we learn, create, and make decisions.

The concepts of Gen-AI are not new mind you, Microsoft rolled out AutoCorrect in MS-Word in 1993.  Apple released Autocorrect with the debut of the iPhone and IOS 1.0.

What’s different is that today’s perfect storm of parallel processing GPU’s, (Related article Microsoft’s own ARM based GPU, look out Nvidia) combined with the neural networking algorithms that can correlate large associations of known language and image results and the open source large language models e.g. Open-AI with its 175B Parameters, all combine to fundamentally change the way we generate content and “original” thought. 

Open-AI’s ChatGPT,  one of the most public and widely used LLM’s stands to either be a breakthrough in the way humans create content or a shortcut to homogenize and normalize the world around marketing doublespeak, depending on your point-of-view.   

Personally, I like the way Google Pixel Image-AI helps everybody take a great picture.

Big-Data is all about using large data sources to form better predictive analytics and facilitate decision making to augment human action that drives better outcomes.

Gen-AI is a giant leap in the same direction, using those same Big-Data concepts but to change the way ideas are formed and content is created. 

The dilemma is that this is the essence of creativity and what makes us human.

 

 

Sam Altman's Commitment: San Francisco's Gen-AI Renaissance Through OpenAI

 In the ever-evolving landscape of Silicon Valley, decisions made by key industry players can have profound effects on the trajectory of both individual companies and the broader tech ecosystem. Sam Altman's recent decision to remain at the helm of OpenAI is not just a crucial move for the organization; it holds promising implications for the thriving Gen-AI scene in San Francisco. In this article, I delve into how Altman's choice to stay is poised to be a catalyst for the continued growth and innovation of the city's tech sector.

Leadership Stability and Vision:

Altman, a respected figure in the tech community, brings a wealth of experience and strategic vision to OpenAI. His decision to stay and board victory at OpenAI signals a long-term commitment to the organization's goals. His leadership continuity is not only vital for OpenAI's trajectory but also fosters an environment of trust and confidence among employees, investors, collaborators, and the broader tech community that lives in the wake of OpenAI. Startups are seeing Gen-AI as a tipping point in areas like: Content Management, Trust Catalogs and Enterprise Knowledge Management.  As San Francisco thrives on innovation and vision, Altman's unwavering commitment contributes significantly to the city's reputation as a global tech investment hub.

Attracting and Retaining Talent:

The war for talent in the tech industry is intense, and a stable leadership team is a powerful magnet for coveted engineers. Altman's decision to stay at OpenAI solidifies the organization as an attractive destination for top-tier talent. This, in turn, benefits San Francisco as a whole, as the influx of skilled individuals contributes to the city's vibrant and dynamic workforce.

Investment Magnet:

A stable leadership team is crucial for attracting investment, and Altman's decision enhances OpenAI's appeal to investors seeking long-term partnerships. The financial stability and strategic vision demonstrated by Altman contribute to a positive investment climate in San Francisco. As OpenAI continues to push the boundaries of artificial intelligence, the city stands to benefit from increased investment flows, fostering an environment where startups and established companies alike can access the capital needed for growth and innovation.

Khosla Ventures is in the final stages of raising $3 billion for its latest set of venture funds, showing how investors remain bullish even as startups continue to stare down slower growth and lower valuations.

in 2019 KV invested $50 million in OpenAI, making it the first outside investor in the company. That investment was more than double the largest first check Khosla Ventures had ever written for a startup.

Inspiring Entrepreneurial Spirit:

Altman's decision to stay at OpenAI serves as a beacon of inspiration for aspiring entrepreneurs in San Francisco. It showcases the potential for long-term success and impact in the tech industry, encouraging the entrepreneurial spirit that defines the city. The success of OpenAI under Altman's leadership sends a positive signal to startups, motivating them to pursue ambitious goals and contribute to the city's reputation as a hotbed of innovation.

Conclusion:

Sam Altman's choice to remain at the helm of OpenAI is not just a decision for the organization; it's a strategic move that radiates positive effects throughout the tech ecosystem of San Francisco. Through leadership stability, talent attraction, increased investment, collaborative initiatives, and inspiration for entrepreneurs, Altman's decision positions both OpenAI and the city as central players in the ongoing narrative of technological innovation. As San Francisco continues to evolve, Altman's commitment provides a solid foundation for the city's tech renaissance.

One App to Rule them All…

 

One App to Rule them All…

In the beginning, frustrated IT Directors, B2B Sellers and Purveyors of Sales and MarTech stacks stitched together Video Collaboration, Conversational Analytics and Scheduling from a myriad of expensive tools like: Zoom, Gong and Calendly. 

But users often found these tools cumbersome, buggy, and expensive.  These tools frustrated users and IT admins alike with tool fatigue, complexity and often performance. These tools taken on their own are also expensive and frankly they don’t need to be.

We failed to address the fundamental needs of simplicity, ease of use and performance in a cost-effective experience that delivers Video Collaboration, Conversational Analytics and Scheduling all in one App. 

One App where you can control your own personal and corporate branding with custom tailored URL’s.  Your own “Digital Virtual Office” where customers can always connect with you instantaneously if you’re available now, leave you a personalized video message to inform you of their need for a conversation and even instantly find a time to connect if you’re away.

The time is now for CollabNow’s All in one Virtual Digital office.

Did I mention that it’s free forever? Yes, FOREVER. 

What are you waiting for? Claim your DVO today and become the Super Hero you were meant to be.

 

 

Customer Experience, the new Battle Front

Commoditization is everywhere.  With offshore development, noisy marketing channels, worldwide internet commerce, the last true battle front that remains is the Customer Experience (Cx).

Today’s buyer, either B2B or B2C (Which is becoming less and less relevant. More on that later) values service and convenience many times over price and product and expectations have never been higher.

Take Uber and Lyft.  Both ride sharing services offer exactly the same thing.  Get me from point A to B in somebody else’s Hyundai Sonata.  What’s the difference? Switching cost is zero.  Customers will churn over a 3-minute wait time.  The difference is the Cx.  How the driver greets you. What happens if you leave your phone in the car?  What is there is a dispute?  How the company handles the Cx defines whether you will renew or churn. Cx drives loyalty.

My friend Nick Mehta has built a great company in Gainsight on Cx being a killer differentiation and managing the Cx is now a whole category unto itself.

The flattening of the product and price curves have driven comprehensive commoditization across broad industries where price and product differentiation were formerly king not just Uber or Lyft, but Boeing or Airbus, eBay or Amazon, Cisco or Juniper. Our parents would drive across town to save 5 cents on a gallon of milk.  Today, I shop at Wholefoods, and am willing pay a premium, for a killer Cx.

Commoditization has flattened differentiation and the only battle front that matters is the Customer Experience. 

Deliver a great Cx and your business will thrive.

Brand Management in the Age of Twitter

In days gone by, a brand interacted with consumers either through retailers or tightly controlled feedback channels.

Brands were separated from their customers and marketing was a “Mad Men” sort of process of smoked filled rooms and catchy slogans and jingles like “Intel Inside”.

The rate of change in the past few years in the way that brands interact with their customers has been exponential with the rise of review sites like Yelp, Trip Advisor, Angie’s List and Twitter with the powerful elegance and beauty of the hashtag.

The hashtag has been the most powerful shift in the loss of B2B anonymity. In the past, if you wanted to complain about bad customer service or a tainted burrito, you were relegated to the black holes of customer service or the complaint department.

Now with a few clicks on your phone, you can bring once powerful brands to their knees as witnessed by Chipotle with a record loss of over $1B in market cap after a sick staffer spread the norovirus around a suburban Washington DC, store, sickening more than 130 customers.

Now powerful tools from Salesforce, Adobe, Lithium and others enable brands to monitor and respond with immediate damage control to prevent billions in loss or increased distribution to capitalize on market inefficiencies.

But the power of the hashtag is not just about angry consumers.  While monitoring its twitter feed shortly after the release of a new LeBron James shoe, Nike noticed that these shoes were being bought up in droves in the Midwest and sold at a 500% mark-up on eBay.  They quickly responded and stepped up production.   When Nintendo was trying to figure out what to do with old outdated games like Donkey Kong, they bundled them onto an old console and listed them for $99. These caught on like wildfire amongst 40 year old gamers looking for childhood nostalgia. Nintendo cranked up production and the price to meet this overwhelming market demand.

Twitter and the power of the hashtag has further accelerated the swing of power from the brand to the consumer.  

Next blog: The power of AI and ML in the new age of brand management. 

Machine Learning is Already in the Palm of your Hand

When most folks think about Machine Learning and Artificial Intelligence, they generally think it’s futuristic science fiction.  iRobot kind of stuff where androids take over the world and a courageous scientist must hack into the central computer to save the planet and restore humanity back on top.

But sometimes some of the best new tech comes disguised as just something really convenient.

You see if you did the iOS10 upgrade to your iPhone, you’re using machine learning right now and probably didn’t even know it.

The machine learning algorithm used by iOS runs natively on your iPhone.  You don’t have to upload your pictures to some High-Performance computing cluster in the sky.  When you take a picture, a lot of really cool things happen.  iOS tags that photo with the location and time.  Simple stuff given the GPS.

But iOS also runs each photo through about 10 Billion (According to Apple) calculations so iOS can recognize faces in your photos and group by person, but it also has advanced object recognition, making it possible to find images of any number of different things. Your little iPhone knows if you have taken pictures of food, cats, dogs, trees and automatically tags meta-data to your pictures for instant retrieval by those search criteria.


OK joke time, Question: What did Will Rogers say to the computer scientist? 


Answer: I never Meta-Data I didn't like.  Ugh. Sorry about that.

In my prior Blog The Fourth Industrial Revolution is Here and Why Google is Getting it Right I touched on how Google’s image and Video API’s were using the virtually unlimited horsepower of the Google Cloud to dissect videos and images pumped up to the Google Cloud to detect Great Danes from Poodles but to classify both as dogs.

Well with iOS10, your iPhone can do pretty much the same thing.

Here’s how to access it.  Go to your Photo Collections and click on the Search Icon. 

Up will pop a search bar and keyboard.  Simply type in the text of the image you want to search for.  In the first case, “Cats”. and IOS will use the predefined meta-data tags automatically associated with the images.  iOS gathers up “Cat” related images and presents you with the below collection.

Ridiculously simple. Machine Learning for the masses and the democratization of what was once highly advanced computer science in the palm of your hand.

Transforming from a Product to a Platform Company

For 20+ years I’ve dedicated a large part of my career to stewarding the evolution of organizations as they transition from a product focused company to a platform.

Recently I’ve been asked about my definition of a platform? Why is it an important step in the evolution of a company and what is the role Business Development plays in that transition?

I’ll do my best to answer those questions in this Blog.

I got hooked on the movement early on when the godfather of multi-tiered architectures,

Alfred Chuang said: “The strength of any platform is defined by the number of partners standing on it”.  At the time, Alfred was CEO of BEA Systems a young, scrappy Java App server company. Alfred knew that to outpace IBM in the JVM market, he had to assemble the best set of partners building on top of his platform.

As we look at the rise of a few notable platforms in the past decade, patterns begin to form.

Facebook – When Facebook broke away from challengers like:  MySpace, Friendster, AOL, etc. there was a few noteworthy differences.  Building your online profile in Facebook is a simple point, click and upload some pictures into a predefined template. The customization model in Facebook is a simple process. MySpace on the other hand, had limitless combinations of presentation options and was

customized via HTML Tags. Great for geeks.  Bad for grandma.  The second compelling feature of Facebook is the ability for third party apps to target the growing community of users with very specific messages based on massive amounts of personalization data. Personalization data, on not just where you were born, went to school, your major, where you work, where you’ve lived, visited and what you ‘Like”, but your entire network of fiends, their profiles and so on and so on.  The flywheel effect kicks in when you can invite partners to build an app on Facebook.  Apps like Spotify, Airbnb, LiveNation etc.  The fourth key attribute that Facebook also has the pole position on is the control point as they stand as the gatekeeper to all your news feeds, interactions with friends, life chronology etc.

iPhone – One of the greatest platforms on the planet.  The commonalities to Facebook are resounding.  Easy, standardized, custom development model.  Massive installed base of loyal customers.  A multitude of persona’s and usage models.  Now every company must have their own customized iPhone app to: 1) Access the throngs of iPhone enthusiasts who crave the standardized UI and User Experience( UX) that is uniquely iPhone. 2) take advantage of the personalization data that is captured by iPhone e.g. your location, places you visit, place you call home, who you communicate with, your browser history, who you transact with etc.

iPhone has a very rigid app development model that takes advantage of platform services like a camera, GPS, microphone, motion accelerometers.  Using the platform features in a structured, certified dev environment has enabled 1000’s of aps in gaming, travel, finance, music, sports, affinity groups and commerce.

To recap the key attributes of a platform:

• Community – Scores of happy users of an anchor tenant app.  You must have this first to entice developers.
• Customization Model – An app dev environment enabling developers to consume rich services served up by your platform.
• Third Party Apps – A wide range of apps built on the extensible customization model consuming platform services.  These apps are often certified by you to make sure they are addressing all of the platform features in a correct manner.
• Control Point – A controlling layer that serves as a centralized information bus for either data, experience or both. When developers use your control layer to access critical data or drive the UX, your platform becomes ultimately sticky.

Transform your Company

Most companies start with a great product idea.  This singular product takes them to being a successful product company with traditional engineering, marketing, and sales. The total addressable market (TAM) of that company is gated by the market size of that one product.  Case in Point – VisiCalc.  Before there was Excel there was VisiCalc from VisiCorp.  This early spreadsheet program, first released in 1979, was originally exclusively for the Apple II.  It was seen as a the “Killer App” for the Apple II. In effect the reason to be for this new compute platform.  People were known to buy the $2,000 Apple II to run a $100 VisiCalc Spreadsheet program. VisiCalc was originally marketed to financial professionals who were looking to use the Apple II. Sold through boutique computer stores, the small TAM, and narrow channel resulted in about 700,000 units sold in six years.

In 1988, Microsoft released Office.  It included Word, Excel and PowerPoint as a bundle. Really it was just marketing three separate disks, installs and apps as one suite.  It had a customization language in Visual Basic for Applications (VBA), enabling user-defined

functions (UDFs), automating processes and accessing Windows API and other low-level functionality through dynamic-link libraries (DLLs). It joined and replaced the abilities of earlier application-specific macro programming languages such as Word's WordBasic. It can be used to control many aspects of the host application, including manipulating user interface features, such as menus and toolbars, and working with custom user forms or dialog boxes.

Suddenly the TAM that Microsoft was addressing was much broader.  Not just financial pro’s, but writers, presenters, collaborators. This new set of knowledge workers demanded a suite of apps that were integrated and had dynamic data transfer for building graphs in Excel and having them auto appear in Word or PowerPoint presentations.  The ability to customize and control all of the apps via VBA brought in third party app developers eager to build apps on top of the Microsoft platform. Combine the power of the platform with multi-channel sales e.g. resellers, online, direct, Fast forward to today.  Microsoft has sold over one billion licenses of Office.  That’s 1 for every 7 people on the planet.

Business Development


An interesting organizational change happens when you decide to shift from being a product company to a platform company.  Business Development (BD) takes a center role in the org. As a single product company, BD was probably focused on providing leadership for Systems Integration partners (SI’s) to assist in successfully deploying your product for customers and maybe integrating your product with existing or third party apps.  An

important function but one that changes dramatically as you become a platform company.

To validate you as a platform company, BD takes on much broader functions:

App Developer Communities – This is a 1:Many function where platform API’s are exposed and supported by partner oriented engineers.  Engineers who are versed in your platform and the multitude of partner app use cases that can delivered by using your platform service.  Exposing your services into popular dev communities Integrated Development environments (IDE’s) like Visual Studio, Eclipse, and run-time execution environments e.g. EJB’s, Ruby, Google App Engine, AWS AMI’s and Lambda, Containers, etc. making sure your platform Software Development Toolkit (SDK) supports the permutations of IDE and run-time environment.

Co-innovation -  This is a 1:Few function where select ISV’s are identified as lighthouse apps to integrate to, build on top of and even OEM your platform because of its unique control point in the stack or UX. The key is to define and co-innovate on a joint solution that is unique to your and only your platform and then keep that integration fresh and ahead of the other platform competitors. The BD teams engage with these ISV’s for a more intimate discussion that probably includes some of the deeper engagements described below. Many times these ISV’s are singled out by the product or sales teams because of their prominence in a market space, geography or industry vertical.  E.g. Schlumberger in Oil and Gas, GE and Siemens in healthcare etc.

Co-Marketing – Once a joint solution is defined the 1:Few Go-to-Market (GTM) plan put in place, invariably contains Co-Marketing. Doesn’t matter if you’re a 10 person start-up or IBM, your contact lists and the numbers of times you can hit these before people opt-out is finite. Partners often have different installed bases than you. Partners leverage each other to market to those installed basses.  Leverage is garnered by leveraging each other’s brand equity.  People are much more likely to respond to a Call to Action (CTA) from a brand they recognize than one unknown to them. Exhibiting at each other’s users conferences and trade  shows brings in a whole new audience.  Even something as simple as a joint press release can be impactful in an over-saturated world.


Co-Selling – This is when things get interesting.  Now that the sales teams have something that is unique, compelling and differentiated to discuss with customers, it’s time to do the account mapping and joint selling.  This is generally done on a grass roots level region by region, rep by rep, account by account. Quota buckets,  accelerators, Sales Promotion Incentive Funds (SPIFS) all determine

how reps focus their energies. As the life blood of their W2, reps are extremely protective of their accounts, so letting another partner in for a pitch is often an exercise fraught with risk.  But as is often the case in many B2B relationships, knowledge displaces fear and replaces it with trust. Understanding how your counterparts are goaled and compensated is critical.

Co-Delivery – 3:few. This is the final mile of a true GTM partnership.  When two product companies come together, what’s often overlooked is actually the most important aspect and that’s customer success.  Solutions, especially joint solutions require specialized expertise and focused alignment with key SI’s that are well versed in the joint solution and have the same obsession towards customer success as the ISV’s.  The further they get away from your own core product, your own Proserv org's expertise will diminish. Partners aligned for your mutual success are key here.
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The rewards for making the difficult transition from a product company to a platform company are significant.  With all its interconnections and eco-systems supporting it, your platform becomes infinitely stickier, customers are far less likely to displace your platform for a whim of pricing or functionality.  Your long-term revenue and market cap will reflect the widened TAM.  Just ask Facebook, Amazon, Google, Microsoft, Apple and the host of other iconic brands that have successfully made the turn and have dominated.