What to do when large language models fail? 

With large language models, it was all promise, no delivery for some companies. How can this be solved in 2025? A key solution might be to take advantage of custom-made small language models (SLMs). This month's newsletter showcases the impact of SLMs and also dives into the benefits data engineering can bring to an organization. 

RECOMMENDED ARTICLES:

2025 will be the year of small language models | by Piotr Kalinowski

Many companies are beginning to realize that while AI solutions can offer great potential, they can only succeed if matched with the right project. This is why small language models (SLMs) are becoming so important. These custom models, which are lighter versions of large language models, can deliver significant advantages for your business.

Data engineering high-level view | by Piotr Jachimczak

The Big Data market size, currently at $84 billion USD, is projected to reach $103 billion USD by 2027. However, the landscape of data-related topics has become significantly more complex than just a decade ago. The key to navigating this complexity is to gain a high-level understanding of modern data analysis. This article will help. 

INDUSTRY INSIGHTS:

The tech industry will grow in 2025 | Forecast 

2025 is expected to see significant growth in the tech industry. According to Canalys' IT Opportunity update, worldwide IT spending is projected to increase by 8.3%, reaching $5.44 trillion USD, including expenditures on software, telecommunications services, and IT services. This growth builds upon the anticipated expansion in 2024, which is forecasted to rise by 7.7%, marking the most substantial growth rate since the post-COVID technology boom. Read the forecast

ROI for investing in AI | Report   

IDC’s in-depth report, The Business Opportunity of AI, outlines how leading organizations utilize AI. Some interesting facts include that for every $1 a company invests in AI, it sees an average return of $3.50. Additionally, 5% of organizations worldwide achieve an average return of $8 for every dollar invested. Notably, 92% of AI deployments take 12 months or less to implement. More information about the report can be found here.

Scaling your embedded systems | On-demand webinar     

The average length of the product development cycle for IoT products and embedded electronic systems was over 16 months. There are ways companies can shorten their time to market. The answer is Model-View-Presenter (MVP) software architecture that boosts scalability and stability. Check out this on-demand free webinar – hosted by seasoned experts – to see how MVP elevates projects. Watch here

ONE LAST THING:

Software Mind wishes you a joyful holiday season filled with warmth, peace, and well-deserved rest. May the new year bring you continued success, growth, and exciting technological advancements. 

Check our blog for more in-depth articles, insights and reports. 

About Software Mind 

Software Mind engineers software that reimagines tomorrow, by providing companies with autonomous development teams who manage software life cycles from ideation to release and beyond. For over 25 years we’ve been enriching organizations with the talent they need to boost scalability, drive dynamic growth and bring disruptive ideas to life. Our top-notch engineering teams combine ownership with leading technologies, including cloud, AI and data science to accelerate digital transformations and boost software delivery.