Adrian Bridgwater

London, Washington, D.C., United States

Technology Journalist at Freelance

Senior Contributor at Forbes

Technology Journalist (semi-retired 2025) - British : American : European - I track 'developer & data' 🇬🇧 🇺🇸 🇪🇺

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Articles

IFS Puts Hard Hats On ‘Industrial AI’ Workforce

2 days ago | forbes.com | Adrian Bridgwater

Engineer holding helmet on site Road construction For the development of modern transportation ... More systems, Technician worker hold hard hat safety firstgettyProduct differentiation proliferates across all sectors.
Platform Engineering - Sidero Labs: Central IT, now with YAML!

2 days ago | computerweekly.com | Adrian Bridgwater

This is a guest post by Justin Garrison, head of product at Sidero Labs – the company specialises in Kubernetes infrastructure automation, developing tools including Talos Linux, a security-focused operating system designed specifically for Kubernetes deployments and Sidero Omni, a SaaS-for-Kubernetes solution. Garrison writes as follows… Many platform engineering teams are building the wrong thing for the wrong people and they’re building it on infrastructure that all-but-guarantees failure.
MuleSoft Connect AI 2025: Live notes from the keynote

3 days ago | computerweekly.com | Adrian Bridgwater

MuleSoft Connect AI 2025 was hosted in New York this month and the Computer Weekly Developer Network had a front row seat to listen to the keynote. According to an opinion piece written by Andrew Comstock, SVP & GM, MuleSoft at Salesforce, disruptive technologies go hand-in-hand with transformations in business models. For instance, he reminds us, cloud computing fundamentally moved IT cost structures from capital to operational expenditure.
MuleSoft Connect AI: Orchestrating secure & integrated AI agents at scale

3 days ago | techzine.eu | Adrian Bridgwater

MuleSoft hosted an intimate gathering of practitioners and data/developer advocate executives in New York this week to walk attendees through the evolving API landscape and examine the role of interconnectivity in the new world of artificial intelligence.
MuleSoft Connect AI: veilige en geïntegreerde AI-agents op grote schaal coördineren

3 days ago | techzine.nl | Adrian Bridgwater

MuleSoft organiseert deze week in New York een besloten bijeenkomst voor professionals en executives op het gebied van data en ontwikkeling. Deelnemers krijgen een overzicht van het veranderende API-landschap en de rol van interconnectiviteit in de nieuwe wereld van AI.
MuleSoft Connect AI: veilige en geïntegreerde AI-agents op grote schaal coördineren

3 days ago | techzine.be | Adrian Bridgwater

MuleSoft organiseert deze week in New York een besloten bijeenkomst voor professionals en executives op het gebied van data en ontwikkeling. Deelnemers krijgen een overzicht van het veranderende API-landschap en de rol van interconnectiviteit in de nieuwe wereld van AI.
Nutanix: DevOps evolved with centralised control & decentralised delight

3 days ago | computerweekly.com | Adrian Bridgwater

This is a guest post for the Computer Weekly Developer Network written by James Sturrock in his role as director of systems engineering for hybrid multi-cloud computing company Nutanix.
New integration threads are needed to form the data fabric for AI.

4 days ago | forbes.com | Adrian Bridgwater

New data integration threads are needed to weave a stronger data fabric for AI use cases. getty Data demands direction. Left on its own, any information resource is of comparatively little value in and of itself until it is applied to a specific use case, inside a specific application (or other data service) through the specified calculations of an algorithm and under the auspices of a specific set of controls for provisioning, maintenance and management.
AIは「大きいほど賢い」わけじゃない？ LLMとの比較から見る「SLM」の実用性：SLMの基礎をおさらい【前編】

4 days ago | techtarget.itmedia.co.jp | Adrian Bridgwater

LLMはその名が示す通り、膨大なデータを学習しており、高度なパターン認識や分析が可能だ。一方、SLMはより小規模なデータの集合体で、特定の領域や目的に特化するケースが多い。そのため、対象分野でより的確かつ迅速な応答が期待できる。 LLMの持つ知識は広範囲に及び、特定の用途に縛られない汎用（はんよう）性がある。裏を返せば、「文脈に即した理解」がやや曖昧になることもある。SLMは、特定の領域に特化されていることで、分野における複雑な文脈もより正確に解釈できるとされている。こうした文脈適応性に加えて、SLMは軽量であり、必要なコンピューティングリソースは少なく済み、処理の遅延が少ないことから、リアルタイム処理が求められる場面での活用に適している。代表的なSLMとしては以下のようなモデルが挙げられる。 GoogleのLLM「BERT」の軽量版「DistilBERT」 Googleの「Gemma」 AIベンダーMistral AIの「Mistral 7B」 Microsoftの「Phi-3 Mini」 Meta Platformsのオープンソースモデル「Llama 3」...
What To Know About Model Context Protocol

1 week ago | flipboard.com | Adrian Bridgwater

16 hours agoRushing to adopt generative AI can derail your business. Here's what leaders need to know. AI, although established as a discipline in computer science for several decades, became a buzzword in 2022 with the emergence of generative AI. Notwithstanding the maturity of AI itself as a scientific …