Tag: Google

Google’s New Tools Support ‘Value Maxxing’ to Address Organizations’ Growing Concern Over AI ROI and Tokenomics

by Rena Bhattacharyya, posted in Big Data
R. Bhattacharyya

Summary Bullets:

• After a period of ‘token maxxing,’ organizations are looking to reign in and better control inference costs.

• Instead, enterprises are now embracing ‘value-maxxing,’ which focuses on outcomes.
Last week, Google announced several enhancements to Gemini Enterprise designed to help enterprises obtain greater and faster ROI on their AI projects. The improvements address one of the biggest frustrations expressed by organizations today, namely that the benefits promised by AI are taking too long to realize. Companies are clamoring for domain specific solutions in order to speed the deployment, reduce the integration complexity, and increase the value obtained from AI projects. Additionally, business leaders are eager for better tools to help them manage AI costs. They are looking for improved visibility on token use and costs, more proactive spending controls, and more flexible payment options.

On Tuesday, August 25th, Google announced Gemini Enterprise for Financial Services and Gemini Enterprise for Legal. The industry-specific solutions include out-of-the box AI capabilities such as specialized agents that provide shortcuts for directing workflows, data connectors, and sector-optimized models. Reusable packages of instructions teach AI agents to perform specialized tasks that are customized to meet company-specific requirements; connectors link agents to internal systems and data while maintaining access controls; pre-built agents are available to deploy out of the box; and software provider partnerships facilitate industry-specific customization and integration, while avoiding vendor lock-in. Though initially rolled out for the financial services and legal industries, Google plans to offer similar solutions for other industries, including healthcare, life sciences, and professional services.

The following day, August 26th, Google revealed expanded tools for managing AI spending. It announced that Google Antigravity, its AI agent development platform, and Android Studio, for building applications, will now be included in Gemini Enterprise subscriptions. Usage across Antigravity, the platform, and the app rolls up into a single view instead of separate license and billing siloes. Furthermore, Google is providing expanded billing flexibility and new cost management tools for agent workloads across Gemini Enterprise. Customers can purchase a mix of per-seat subscriptions along with a new pay-as-you-go option, to help avoid hitting token caps in the middle of a job. Companies that commit to a minimum monthly spend will receive discounts on token costs. To better control spending, Google has rolled out new guardrails that enable administrators to set limits on AI spend by project, help estimate agent runtime costs, and identify anomalies in spending. Project level guardrails can pause an agent when API call limits are reached; a FinOps agent provides spending summaries in natural language.

Google’s announcements directly address concerns many organizations have over the spend on AI inference. After a period of ‘token maxxing’ wherein greater token usage was associated with greater productivity, organizations are looking to rein in and better control inference costs. Despite declining token costs, overall consumption, and therefore spend, are skyrocketing. Thus, the industry is now embracing ‘value-maxxing,’ which focuses on outcomes. It seeks to identify and quantify results, whether they be improved performance, more insightful decisions, or greater efficiency.

Regardless of the jargon of the day, organizations are taking a more analytical and practical approach to cost, latency, and performance optimization. No longer is the fastest or most expensive model considered the best choice for all tasks; organizations are now recognizing that some workflows are served well enough by less intensive reasoning, and that the same level of accuracy is not required for all tasks. At the same time, many are considering open-source strategies, attracted to the potential of lower costs, ability to fine tune models, greater transparency, local deployment options, and the option of leveraging existing infrastructure investments. At the end of the day, the development of appropriate AI strategies relies heavily on a broader understanding of the business and its operating model; professionals that can combine this knowledge with technical AI expertise are invaluable.

AI and Machine Learning Need Developers More Than Data

by , posted in Big Data

B. Shimmin
B. Shimmin

Summary Bullets:

• Google wants to democratize AI and operationalize machine learning (ML) with the release of Google Cloud Machine Learning Engine, a platform that includes developer-friendly APIs and pre-trained data models.

• But what the company really needs isn’t just data, algorithms or even data scientists but instead a new breed of developers, who can build software that can anticipate outcomes.

It’s always the same at the end of a company’s keynote address. After all of the important messages have been conveyed and all of the product announcements have been made, a mid-level corporate mouthpiece will take the stage and provide the audience with some positive reinforcement of what went before. It’s like the closing credits of a film, something that may contain a nugget of interest to the cinephile. More often, it serves as filler, a thematic soundtrack to accompany attendees as they make for the exits.

Continue reading “AI and Machine Learning Need Developers More Than Data” →

As 2016 Beckons, What Should Telecoms Buyers Look for from UC Solutions?

by Gary Barton, posted in Communicate

G. Barton
G. Barton

Summary Bullets:

• Enterprises should look at vendor platforms beyond Microsoft and Cisco and demand interoperability between platforms and applications.

• Unified communications (UC) and mobility are now intrinsically linked.

2015 has been the year that UC solutions have really started to achieve market traction. Take-up is far from universal, but for most UC features CA’s own research suggests that usage amongst enterprises is above 50%. The uptick in usage is down to a number of factors–for example, falling prices and the maturity of the technology–however, it is the improvement of the business case for UC that seems to have had the biggest impact. Vodafone, for example, has reported a strong response from customers following the development of new proof of concept demonstrations and a new approach to training and educating its workforce. So the initial message for enterprise users is that a conversation with your provider concerning unified communications is likely to be more centred on achieving better business outcomes, and therefore a more worthwhile experience. Continue reading “As 2016 Beckons, What Should Telecoms Buyers Look for from UC Solutions?” →

Google’s Alphabet Shakeup Is a Huge Improvement; I Don’t Like That

by , posted in Big Data

Brad Shimmin
Brad Shimmin

Summary Bullets:

  • With Alphabet now holding the reins of Google, a more traditional, more focused vision should make products like Google Apps for Business more appropriate for the enterprise by introducing a more stable evolution of capabilities.
  • But, with a tighter focus within Google itself, will the industry lose out on what were frequently disruptive, sometimes crazy but quite often game-changing innovations from Google proper?

I’ve had some time to think about the recent corporate reorganization at the company formerly known as Google but now referred to as Alphabet, and while I was initially skeptical, I now truly believe that this move will make products like Google Apps for Business much more appealing to enterprise buyers. With high-value interests like Search, Android, YouTube, Apps, Maps, and Ads all housed within a single corporate entitle (Google), enterprises of all sizes (not just those within the long tail) will be able to look forward to many improvements such as a more consistent and transparent rate of innovation as well as improved cross product synergies… perhaps a [cough!] unified API. Continue reading “Google’s Alphabet Shakeup Is a Huge Improvement; I Don’t Like That” →

Marking HTTP Sites as Insecure: The Emperor’s New Clothes Indeed!

by , posted in Network

Mike Fratto
Mike Fratto

Summary Bullets:

  • Users don’t have a way for readily knowing when a site should be protected using SSL/TLS or not, and Google engineers are proposing yet another indicator.
  • A better use of their time would be in working with existing standards efforts – or starting a new one – that let site owners indicate when a site should be protected.

Google is using its size in the web arena to affect changes in how users view the relative “security” of websites. I put security in scare quotes because that word has a dubious meaning at best and more likely doesn’t mean what the company intends. The short story is that Google wants a way to indicate to end users that a page which is not properly protected using TLS – the current, improved version of SSL – is not secure. Continue reading “Marking HTTP Sites as Insecure: The Emperor’s New Clothes Indeed!” →

What Comes After Enterprise Social Networking? Business Networking

by , posted in Communicate

Brad Shimmin
Brad Shimmin

Summary Bullets:

  • Enterprise social networking is nothing more than a passing fancy, at least in terms of describing the idea of collaboration.
  • For a view into what will follow, we need look no further than our own corporate priorities and the manner in which vendors seek to meet those priorities.

Language is a slippery customer. We mold and evolve words and phrases to meet our expectations of how the world works at any given time. For that reason, words and phrases come and go, depending upon whether or not they fulfill this need. And as I’ve been informed, many of the beloved words from my youth are no longer meaningful, words like preppie, hoser, rad, tubular and of course groupware. Continue reading “What Comes After Enterprise Social Networking? Business Networking” →