22 results for “analyseasia”
Jing Yang grew up using pirated Word—not by choice, but licensed software wasn't sold in China.
That legacy haunts today's AI founders. Enterprise AI is gold in Silicon Valley, yet Chinese entrepreneurs must go consumer-first overseas. The cultural gap around paying for software runs deeper than any model improvement.
VCs hope advanced AI will finally flip the switch. Will it?
Episode Recap: Aneesh Raman, LinkedIn’s Chief Economic Opportunity Officer and co‑author of Open to Work, joins us on “We Never Left the Industrial Age: AI and the Future of Work”. He warns the biggest AI risk isn’t job loss but wealth staying at the top, and shares what individuals, firms and policymakers can do. Listen: https://overcast.fm/+SMFssX62E #AI #FutureOfWork #EconomicInclusion
Attention is a luxury in humanitarian work. In this short, Nur Hafiza Mutalif shares how Singapore Red Cross uses AI to surface forgotten crises—curating complex information, not creating more noise, and helping the public look beyond compassion fatigue.
Watch on YouTube: https://youtube.com/shorts/Pz3ac2jR7tA
On the Analyse Podcast, Aneesh Raman notes that by 2030 70% of the skills in an average job will have changed. Engineers now split time between coding, system syncing and customer talks. Entry-level roles are being lifted with AI fluency and an entrepreneurial mindset. Work isn't ending — it's evolving. #futureofwork https://youtube.com/shorts/EnPOiz8HhXw
"Whatever you think, do the exact opposite." That's Steve Clayton's (Cisco SVP) approach to winning at communications.
The sailboat analogy hits hard: while everyone sails the same direction, one captain spots the wind shift and tacks the opposite way. That's the boat that wins.
How do we earn permission to capture attention instead of blending into the noise?
Watch on YouTube: https://youtube.com/shorts/JfhqFYbnIOs
"The org chart is done." – Aneesh Raman explains why the corporate pyramid crumbled in the AI era. From steam engines to AI, work has always followed tech. Industrial‑age hierarchies prized predictability; today it’s a sprint for innovation. Lead by design, not command – the whole firm feels like a massive startup. Watch the short on YouTube: https://youtube.com/shorts/UNZ-QKLjWcE #opentowork
Why hasn’t China’s AI market consolidated?
Jing Yang is surprised too: while the US has narrowed to a few frontier-model players, China still has ByteDance, Baidu, Alibaba, Tencent—and a deep second tier across language and video models.
Watch on YouTube:
https://youtube.com/shorts/0ayXJjeZ7Og
New episode with Nur Hafiza Mutalif from Singapore Red Cross 🌏
In humanitarian work, AI isn't about efficiency — it's about impact and trust. Cautious adoption isn't lag, it's a do-no-harm standard.
From freeing staff from daily data collation to forecasting leptospirosis in Thailand, hear how trust-first AI partnerships make a real difference.
Watch on YouTube 👇
https://youtu.be/b2OKYwwBxLs?ref=analysepodcast.com
Jing Yang points out the $0 revenue trap squeezing China’s AI startups. Giants like ByteDance and BAT can open‑source thanks to cash‑cow businesses, but labs such as Z.AI and MiniMax struggle when most income comes from one‑off on‑premise deals. The open‑source flywheel fuels user data, leaving smaller players in a crisis.
Watch on YouTube: https://youtube.com/shorts/pCpTgBsH9zo
Most orgs chasing the latest AI model are missing the point entirely.
Sophie Dionnet from Dataiku puts it plainly: the transformation you need today doesn't require the newest model. It requires the hard, unglamorous work of change management.
The real trap? Preferring the new toy over actually putting it to use.
Watch on YouTube: https://youtube.com/shorts/1iSO634q-Lw
Scammers are weaponizing AI to clone voices & fake images—sophisticated attacks we’ve never seen before. But Meta is fighting fire with fire.
In 2025 alone, they removed 159M scam accounts, using AI to analyze billions of signals & dismantle fraud at scale. Dr. Rafael Frankel shares how these systems are evolving into one of cybersecurity’s most powerful shields.
Watch on YouTube: https://youtube.com/shorts/0sJr9AqYnAo
#Meta #CyberSecurity #ArtificialIntelligence #TechPolicy #ScamPrevention
Scammers are using AI to fake voices, images and identities. But in our chat with Dr. Rafael Frankel, we heard the other side: Meta uses AI across billions of signals to spot patterns and remove scam accounts at scale — 159M in 2025 alone.
Watch on YouTube: https://youtube.com/shorts/0sJr9AqYnAo
#Meta #Cybersecurity #ArtificialIntelligence #ScamPrevention
Are we chasing AI progress—or avoiding change?
In our conversation, Sophie Dionnet of Dataiku argues that most organisations don’t need the latest model. The harder work is change management: turning useful technology into real transformation. The trap is choosing the new toy over putting AI to work.
Watch on YouTube: https://youtube.com/shorts/1iSO634q-Lw
#EnterpriseAI #Dataiku #DigitalTransformation #ChangeManagement
AI isn’t magic. In our conversation with Sophie Dionnet (Dataiku), she cuts to the real enterprise AI trap: not models, but change management.
“Taking a decision is one hour, implementation is two years.”
That gap is where AI succeeds or stalls.
Watch on YouTube: https://youtube.com/shorts/Rh2kZ4P_ib4